This document shows how to use and download US Census data to research the underlying drivers of emissions output from industrial facilities across seven states identified as primary contributors to acid rain-related changes at the Hubbard Brook Experimental Forest (HBEF). The aim is to investigate if there is a relationship between wealth inequality and emissions output from these facilities. Census data provides important demographic and economic context, which helps to explore patterns of industrial emissions and their potential connections with socio-economic variables, such as wealth inequality, across regions.
The analysis in this document introduces a series of frameworks that leverage Census data. This section looks at segregation and diversity indices, which help to understand demographic patterns that may correlate with the distribution of industrial emissions.
A large body of research in the social sciences is concerned with
neighborhood segregation and diversity. Segregation generally refers to
the extent to which two or more groups live apart from each other;
diversity measures neighborhood heterogeneity among groups. A wide range
of indices have been developed by social scientists to measure
segregation and diversity, often relying on spatial Census data.
Segregation and diversity indices are implemented in a variety of R
packages; the package recommended by this document is the segregation
package (Elbers 2021), which includes R functions for various regional
and local indices
The data setup below uses spatial methods to acquire Census tract-level data on population estimates for non-Hispanic white, non-Hispanic black, non-Hispanic Asian, and Hispanic populations across the seven states identified as major contributors to acid rain at HBEF: Ohio, Pennsylvania, Tennessee, West Virginia, Kentucky, Indiana, and Illinois. The analysis filters Census tracts that intersect the largest urbanized areas by population in each state using an inner spatial join. This prelminary data exploration uses urbanized areas for 2019 and data from the 2015-2019 ACS. To extend this analysis to multiple states, a vector of state abbreviations is used, iterating over them to append the data for each state.
# Define the states for analysis
states <- c("OH", "PA", "TN", "WV", "KY", "IN", "IL")
# Initialize an empty list to store data for each state
state_data_list <- list()
# Loop through each state to get tract data by race/ethnicity
for (state in states) {
state_data <- get_acs(
geography = "tract",
variables = c(
white = "B03002_003",
black = "B03002_004",
asian = "B03002_006",
hispanic = "B03002_012"
),
state = state,
geometry = TRUE,
year = 2019
)
state_data_list[[state]] <- state_data
}
# Combine data from all states
acs_data <- bind_rows(state_data_list)
# Use tidycensus to get urbanized areas by population with geometry,
# then filter for those that have populations of 100,000 or more
us_urban_areas <- get_acs(
geography = "urban area",
variables = "B01001_001",
geometry = TRUE,
year = 2019,
survey = "acs1"
) %>%
filter(estimate >= 100000) %>%
transmute(urban_name = str_remove(NAME,
fixed(" Urbanized Area (2010)")))
# Compute an inner spatial join between tract data and urbanized areas
urban_data <- acs_data %>%
st_join(us_urban_areas, left = FALSE) %>%
select(-NAME) %>%
st_drop_geometry() %>%
mutate(dataset = "2015-2019 5-year ACS")
# Get tracts for each state and bind them into a single dataset
tracts_data <- bind_rows(
tracts(state = "WV", cb = TRUE, year = 2019),
tracts(state = "PA", cb = TRUE, year = 2019),
tracts(state = "OH", cb = TRUE, year = 2019),
tracts(state = "TN", cb = TRUE, year = 2019),
tracts(state = "KY", cb = TRUE, year = 2019),
tracts(state = "IN", cb = TRUE, year = 2019),
tracts(state = "IL", cb = TRUE, year = 2019)
) %>%
mutate(State = case_when(
STATEFP == "54" ~ "WV",
STATEFP == "42" ~ "PA",
STATEFP == "39" ~ "OH",
STATEFP == "47" ~ "TN",
STATEFP == "21" ~ "KY",
STATEFP == "18" ~ "IN",
STATEFP == "17" ~ "IL"
))
# Display the first few rows using flextable
flextable(urban_data %>% head(10) %>%
dplyr::select(-dataset)) %>%
set_caption("Census Tract-Level Data (Urbanized Areas), 5-year ACS") %>%
autofit() %>%
colformat_num(j = c("estimate", "moe"), digits = 2) %>% # Format numerical columns
set_header_labels(
GEOID = "Census Tract GEOID",
variable = "Population Group",
estimate = "Population Estimate",
moe = "Margin of Error",
urban_name = "Urban Area"
)The spatial analysis workflow uses the following steps: 1. Data on race and ethnicity from the 2015-2019 ACS for the largest demographic groups is acquired at the Census tract level for multiple states. 2. Urban areas for the entire US are obtained, filtered to those with populations of 750,000 or greater. 3. A spatial join between the Census tract data and urban area data is computed, retaining only those Census tracts intersecting the urban area boundaries.
The dissimilarity index is widely used to assess neighborhood segregation between two groups within a region. It ranges from 0 (perfect integration) to 1 (complete segregation). The dissimilarity index (\(D\)) is calculated as follows:
The dissimilarity index (\(D\)) is calculated as follows:
\[ D = \frac{1}{2} \sum_{i=1}^{N} \left| \frac{a_i}{A} - \frac{b_i}{B} \right| \]
Where: - \(a_i\) represents the population of group A in a given unit \(i\) - \(A\) is the total population of group A in the region - \(b_i\) represents the population of group B in a given unit \(i\) - \(B\) is the total population of group B in the region
The dissimilarity index can be computed using the dissimilarity()
function from the segregation package.
# Compute dissimilarity index between Black and white populations
dissimilarity_index_data_black_white <- urban_data %>%
filter(variable %in% c("white", "black")) %>%
group_by(urban_name) %>%
group_modify(~
dissimilarity(.x,
group = "variable",
unit = "GEOID",
weight = "estimate"
)
) %>%
arrange(desc(est))
# Present results in a table
flextable(dissimilarity_index_data_black_white) %>%
set_caption("Dissimilarity Index between Black and White Populations") %>%
colformat_num(j = c("est"), digits = 3) %>%
set_header_labels(
urban_name = "Urban Area",
stat = "Statistic",
est = "Dissimilarity Index Estimate"
) %>%
autofit()Urban Area | Statistic | Dissimilarity Index Estimate |
|---|---|---|
Chicago, IL--IN | D | 0.7484 |
Philadelphia, PA--NJ--DE--MD | D | 0.7325 |
Cleveland, OH | D | 0.7298 |
Peoria, IL | D | 0.6811 |
Memphis, TN--MS--AR | D | 0.6596 |
Cincinnati, OH--KY--IN | D | 0.6552 |
Pittsburgh, PA | D | 0.6551 |
Harrisburg, PA | D | 0.6395 |
Akron, OH | D | 0.6300 |
Dayton, OH | D | 0.6294 |
Youngstown, OH--PA | D | 0.6249 |
Indianapolis, IN | D | 0.6238 |
Erie, PA | D | 0.6100 |
Toledo, OH--MI | D | 0.5944 |
Columbus, OH | D | 0.5720 |
Canton, OH | D | 0.5665 |
Johnson City, TN | D | 0.5651 |
Chattanooga, TN--GA | D | 0.5624 |
St. Louis, MO--IL | D | 0.5611 |
Fort Wayne, IN | D | 0.5583 |
Scranton, PA | D | 0.5577 |
Knoxville, TN | D | 0.5549 |
Rockford, IL | D | 0.5500 |
South Bend, IN--MI | D | 0.5484 |
Charleston, WV | D | 0.5427 |
Lancaster, PA | D | 0.5415 |
Louisville/Jefferson County, KY--IN | D | 0.5399 |
Nashville-Davidson, TN | D | 0.5312 |
Pottstown, PA | D | 0.5272 |
Springfield, IL | D | 0.5261 |
Huntington, WV--KY--OH | D | 0.5195 |
York, PA | D | 0.5130 |
Elkhart, IN--MI | D | 0.5102 |
Allentown, PA--NJ | D | 0.5062 |
Reading, PA | D | 0.5047 |
Evansville, IN--KY | D | 0.4931 |
Davenport, IA--IL | D | 0.4881 |
Kenosha, WI--IL | D | 0.4819 |
Round Lake Beach--McHenry--Grayslake, IL--WI | D | 0.4701 |
Lorain--Elyria, OH | D | 0.4687 |
Lexington-Fayette, KY | D | 0.4627 |
Champaign, IL | D | 0.4034 |
Bloomington--Normal, IL | D | 0.3644 |
Bloomington, IN | D | 0.3391 |
Lafayette, IN | D | 0.3318 |
Murfreesboro, TN | D | 0.3285 |
Clarksville, TN--KY | D | 0.3076 |
Hagerstown, MD--WV--PA | D | 0.2474 |
Binghamton, NY--PA | D | 0.2178 |
Trenton, NJ | D | 0.0000 |
# Compute dissimilarity index between non-Hispanic white and Hispanic populations
dissimilarity_index_data_hispanic_white <- urban_data %>%
filter(variable %in% c("white", "hispanic")) %>%
group_by(urban_name) %>%
group_modify(~
dissimilarity(.x,
group = "variable",
unit = "GEOID",
weight = "estimate"
)
) %>%
arrange(desc(est))
print(dissimilarity_index_data_hispanic_white)## # A tibble: 50 × 3
## # Groups: urban_name [50]
## urban_name stat est
## <chr> <chr> <dbl>
## 1 Reading, PA D 0.636
## 2 Memphis, TN--MS--AR D 0.589
## 3 Philadelphia, PA--NJ--DE--MD D 0.573
## 4 Allentown, PA--NJ D 0.563
## 5 Chicago, IL--IN D 0.553
## 6 Erie, PA D 0.517
## 7 Youngstown, OH--PA D 0.510
## 8 Cleveland, OH D 0.503
## 9 York, PA D 0.496
## 10 Scranton, PA D 0.489
## # ℹ 40 more rows
# Present results in a table
flextable(dissimilarity_index_data_hispanic_white) %>%
set_caption("Dissimilarity Index between Hispanic and White Populations") %>%
colformat_num(j = c("est"), digits = 3) %>%
set_header_labels(
urban_name = "Urban Area",
stat = "Statistic",
est = "Dissimilarity Index Estimate"
) %>%
autofit()Urban Area | Statistic | Dissimilarity Index Estimate |
|---|---|---|
Reading, PA | D | 0.6364 |
Memphis, TN--MS--AR | D | 0.5889 |
Philadelphia, PA--NJ--DE--MD | D | 0.5730 |
Allentown, PA--NJ | D | 0.5631 |
Chicago, IL--IN | D | 0.5529 |
Erie, PA | D | 0.5166 |
Youngstown, OH--PA | D | 0.5105 |
Cleveland, OH | D | 0.5034 |
York, PA | D | 0.4965 |
Scranton, PA | D | 0.4892 |
Lorain--Elyria, OH | D | 0.4855 |
Fort Wayne, IN | D | 0.4840 |
Nashville-Davidson, TN | D | 0.4827 |
Indianapolis, IN | D | 0.4798 |
Huntington, WV--KY--OH | D | 0.4765 |
Lancaster, PA | D | 0.4589 |
Charleston, WV | D | 0.4531 |
South Bend, IN--MI | D | 0.4516 |
Akron, OH | D | 0.4489 |
Harrisburg, PA | D | 0.4468 |
Chattanooga, TN--GA | D | 0.4416 |
Cincinnati, OH--KY--IN | D | 0.4383 |
Columbus, OH | D | 0.4331 |
Peoria, IL | D | 0.4238 |
Lexington-Fayette, KY | D | 0.4137 |
Rockford, IL | D | 0.4076 |
Evansville, IN--KY | D | 0.4038 |
Canton, OH | D | 0.4007 |
Elkhart, IN--MI | D | 0.3995 |
Louisville/Jefferson County, KY--IN | D | 0.3976 |
Pittsburgh, PA | D | 0.3883 |
Springfield, IL | D | 0.3858 |
Round Lake Beach--McHenry--Grayslake, IL--WI | D | 0.3759 |
Knoxville, TN | D | 0.3757 |
Dayton, OH | D | 0.3710 |
Johnson City, TN | D | 0.3673 |
St. Louis, MO--IL | D | 0.3628 |
Toledo, OH--MI | D | 0.3424 |
Davenport, IA--IL | D | 0.3393 |
Bloomington, IN | D | 0.3317 |
Bloomington--Normal, IL | D | 0.3265 |
Murfreesboro, TN | D | 0.3254 |
Clarksville, TN--KY | D | 0.3223 |
Lafayette, IN | D | 0.3089 |
Binghamton, NY--PA | D | 0.2939 |
Pottstown, PA | D | 0.2910 |
Champaign, IL | D | 0.2402 |
Hagerstown, MD--WV--PA | D | 0.2152 |
Kenosha, WI--IL | D | 0.1627 |
Trenton, NJ | D | 0.0000 |
One disadvantage of the dissimilarity index is that it only measures segregation between two groups, the above code shows the dissimilarity index between white and Hispanic and white and Black populations in the identified states.
Computing multi-group indices is achieved using the segregation
package. To measure segregation and diversity across multiple groups, we
use the mutual_within() function computes indices like the Mutual
Information Index (M) and Theil’s Entropy Index (H).
The Mutual Information Index (\(M\)) is computed as follows (Elbers, 2021):
\[ M(T) = \sum_{u=1}^{U} \sum_{g=1}^{G} p_{ug} \log \frac{p_{ug}}{p_u p_g} \]
Where: - \(U\) is the total number of units - \(G\) is the total number of groups - \(p_{ug}\) is the joint probability of being in unit \(u\) and group \(g\)
Theil’s Entropy Index (\(H\)) is calculated as (Mora and Ruiz-Castillo, 2011):
\[ H(T) = \frac{M(T)}{E(T)} \]
Where \(E(T)\) is the entropy of the dataset, normalizing \(H\) to range between values of 0 and 1.
# Compute multi-group segregation indices
multigroup_indices <- mutual_within(
data = urban_data,
group = "variable",
unit = "GEOID",
weight = "estimate",
within = "urban_name",
wide = TRUE
)
# present the results in a table
flextable(multigroup_indices %>% head(15)) %>%
set_caption("Multi-Group Segregation Indices by Urban Area") %>%
colformat_num(j = c("M", "p", "H", "ent_ratio"), digits = 3) %>%
set_header_labels(
urban_name = "Urban Area",
M = "Mutual Information (M)",
p = "Proportion (p)",
H = "Entropy (H)",
ent_ratio = "Entropy Ratio"
) %>%
autofit()Urban Area | Mutual Information (M) | Proportion (p) | Entropy (H) | Entropy Ratio |
|---|---|---|---|---|
Akron, OH | 0.169103 | 0.0173495 | 0.28950 | 0.6300 |
Allentown, PA--NJ | 0.179233 | 0.0205808 | 0.23064 | 0.8382 |
Binghamton, NY--PA | 0.006391 | 0.0002773 | 0.05433 | 0.1269 |
Bloomington, IN | 0.061115 | 0.0037081 | 0.11146 | 0.5914 |
Bloomington--Normal, IL | 0.069118 | 0.0042043 | 0.09682 | 0.7700 |
Canton, OH | 0.095663 | 0.0093755 | 0.22571 | 0.4572 |
Champaign, IL | 0.136618 | 0.0042517 | 0.13280 | 1.1096 |
Charleston, WV | 0.072811 | 0.0056961 | 0.19668 | 0.3993 |
Chattanooga, TN--GA | 0.213702 | 0.0094675 | 0.26708 | 0.8631 |
Chicago, IL--IN | 0.438394 | 0.2347320 | 0.37413 | 1.2639 |
Cincinnati, OH--KY--IN | 0.209106 | 0.0479094 | 0.30302 | 0.7443 |
Clarksville, TN--KY | 0.076244 | 0.0054987 | 0.07999 | 1.0281 |
Cleveland, OH | 0.326898 | 0.0509027 | 0.39937 | 0.8829 |
Columbus, OH | 0.208010 | 0.0426960 | 0.23622 | 0.9498 |
Davenport, IA--IL | 0.126018 | 0.0040899 | 0.15933 | 0.8531 |
# Calculate local segregation indices
local_segregation_indices <- urban_data %>%
mutual_local(
group = "variable",
unit = "GEOID",
weight = "estimate",
wide = TRUE
)
# Present local segregation indices
flextable(local_segregation_indices) %>%
set_caption("Local Segregation Indices by Census Tract") %>%
colformat_num(j = c("ls", "p"), digits = 5) %>%
set_header_labels(
GEOID = "Census Tract GEOID",
ls = "Local Segregation Index (ls)",
p = "Proportion (p)"
) %>%
autofit()Census Tract GEOID | Local Segregation Index (ls) | Proportion (p) |
|---|---|---|
17007010100 | 0.401218 | 0.0002023044 |
17007010200 | 0.269342 | 0.0001634530 |
17007010300 | 0.385884 | 0.0001796298 |
17007010400 | 0.171788 | 0.0001788957 |
17007010500 | 0.177973 | 0.0002794362 |
17007010601 | 0.241287 | 0.0001033952 |
17007010602 | 0.073872 | 0.0003204897 |
17019000200 | 0.943404 | 0.0000507052 |
17019000301 | 0.304861 | 0.0001359662 |
17019000302 | 1.120082 | 0.0000715039 |
17019000401 | 0.308713 | 0.0001387665 |
17019000402 | 0.142073 | 0.0001118234 |
17019000500 | 0.057330 | 0.0001011114 |
17019000700 | 0.124053 | 0.0000841190 |
17019000800 | 0.188129 | 0.0001650843 |
17019000901 | 0.375315 | 0.0001355584 |
17019000902 | 0.046774 | 0.0001799560 |
17019001000 | 0.125515 | 0.0001172610 |
17019001100 | 0.047190 | 0.0000977129 |
17019001201 | 0.120210 | 0.0001768022 |
17019001203 | 0.047426 | 0.0001308005 |
17019001204 | 0.307643 | 0.0001042380 |
17019001205 | 0.278896 | 0.0001941752 |
17019001206 | 0.084887 | 0.0000554903 |
17019001301 | 0.063861 | 0.0001668787 |
17019001302 | 0.192637 | 0.0001195991 |
17019001400 | 0.296565 | 0.0001813426 |
17019005300 | 0.577137 | 0.0001440681 |
17019005401 | 0.028646 | 0.0001149500 |
17019005402 | 0.070371 | 0.0000935804 |
17019005500 | 0.025896 | 0.0001263417 |
17019005600 | 0.027407 | 0.0001875686 |
17019005701 | 0.038886 | 0.0001318064 |
17019005702 | 0.266121 | 0.0000909976 |
17019005800 | 0.138622 | 0.0001001870 |
17019005900 | 0.460765 | 0.0001623927 |
17019006000 | 0.424573 | 0.0000941513 |
17019010604 | 0.235767 | 0.0000628310 |
17019010900 | 0.202306 | 0.0002493665 |
17019011000 | 0.033470 | 0.0001144606 |
17019011100 | 0.633577 | 0.0000600578 |
17031010100 | 0.261512 | 0.0001214479 |
17031010201 | 0.267014 | 0.0001839798 |
17031010202 | 0.299388 | 0.0000750655 |
17031010300 | 0.128723 | 0.0001688634 |
17031010400 | 0.013687 | 0.0001386034 |
17031010501 | 0.116221 | 0.0001054887 |
17031010502 | 0.054898 | 0.0000817265 |
17031010503 | 0.093802 | 0.0000472524 |
17031010600 | 0.087745 | 0.0001689450 |
17031010701 | 0.175266 | 0.0000976314 |
17031010702 | 0.278950 | 0.0001352049 |
17031020100 | 0.286537 | 0.0000936891 |
17031020200 | 0.206919 | 0.0001775635 |
17031020301 | 0.121155 | 0.0001416756 |
17031020302 | 0.088924 | 0.0001323230 |
17031020400 | 0.193530 | 0.0001104640 |
17031020500 | 1.031769 | 0.0001701412 |
17031020601 | 0.375577 | 0.0001682381 |
17031020602 | 0.362149 | 0.0001271029 |
17031020701 | 0.163935 | 0.0000492915 |
17031020702 | 0.458535 | 0.0002211727 |
17031020801 | 0.570757 | 0.0001571727 |
17031020802 | 0.636000 | 0.0001862364 |
17031020901 | 0.532747 | 0.0001580698 |
17031020902 | 0.397462 | 0.0001298217 |
17031030101 | 0.236526 | 0.0001030961 |
17031030102 | 0.100694 | 0.0000713408 |
17031030103 | 0.061553 | 0.0000578013 |
17031030104 | 0.123069 | 0.0000905897 |
17031030200 | 0.055491 | 0.0001506748 |
17031030300 | 0.318750 | 0.0000949942 |
17031030400 | 0.199705 | 0.0000675617 |
17031030500 | 0.105851 | 0.0001748447 |
17031030601 | 0.249586 | 0.0000898285 |
17031030603 | 0.201331 | 0.0000629941 |
17031030604 | 0.248083 | 0.0000985014 |
17031030701 | 0.106914 | 0.0000428480 |
17031030702 | 0.412632 | 0.0000581275 |
17031030703 | 0.019569 | 0.0000781105 |
17031030706 | 0.168851 | 0.0000768327 |
17031030800 | 0.108661 | 0.0001108990 |
17031030900 | 0.063499 | 0.0000817265 |
17031031000 | 0.086899 | 0.0001045099 |
17031031100 | 0.115195 | 0.0001233238 |
17031031200 | 0.321507 | 0.0001667428 |
17031031300 | 0.198684 | 0.0002076604 |
17031031400 | 0.087213 | 0.0001302567 |
17031031501 | 0.265413 | 0.0001192457 |
17031031502 | 0.250075 | 0.0001222635 |
17031031700 | 0.022508 | 0.0001772916 |
17031031800 | 0.106501 | 0.0000502702 |
17031031900 | 0.026143 | 0.0000655770 |
17031032100 | 0.085078 | 0.0001869705 |
17031040100 | 0.120199 | 0.0001096212 |
17031040201 | 0.153662 | 0.0001777266 |
17031040202 | 0.278538 | 0.0001895805 |
17031040300 | 0.514401 | 0.0000784368 |
17031040401 | 0.136393 | 0.0000849075 |
17031040402 | 0.109128 | 0.0001339815 |
17031040600 | 0.085264 | 0.0000680511 |
17031040700 | 0.114795 | 0.0000868650 |
17031040800 | 0.090214 | 0.0000425761 |
17031040900 | 0.135669 | 0.0000502159 |
17031050100 | 0.097534 | 0.0000706067 |
17031050200 | 0.123510 | 0.0001314802 |
17031050300 | 0.223635 | 0.0000663926 |
17031050500 | 0.189426 | 0.0001548345 |
17031050600 | 0.198263 | 0.0000574750 |
17031050700 | 0.214693 | 0.0000464096 |
17031050800 | 0.100044 | 0.0000369482 |
17031050900 | 0.189708 | 0.0000372473 |
17031051000 | 0.192519 | 0.0000486118 |
17031051100 | 0.132557 | 0.0000436636 |
17031051200 | 0.055879 | 0.0000401020 |
17031051300 | 0.114923 | 0.0000766424 |
17031051400 | 0.045109 | 0.0000537503 |
17031060100 | 0.063367 | 0.0000760715 |
17031060200 | 0.133324 | 0.0000589431 |
17031060300 | 0.128447 | 0.0000777299 |
17031060400 | 0.150930 | 0.0001023077 |
17031060500 | 0.139578 | 0.0000320816 |
17031060800 | 0.108364 | 0.0001293867 |
17031060900 | 0.029893 | 0.0001949093 |
17031061000 | 0.123304 | 0.0000589975 |
17031061100 | 0.126272 | 0.0000370026 |
17031061200 | 0.127914 | 0.0000563331 |
17031061500 | 0.144445 | 0.0000522549 |
17031061800 | 0.093823 | 0.0000357520 |
17031061901 | 0.230917 | 0.0000932813 |
17031061902 | 0.159266 | 0.0001263145 |
17031062000 | 0.108204 | 0.0000780018 |
17031062100 | 0.084463 | 0.0000988820 |
17031062200 | 0.143410 | 0.0000812371 |
17031062300 | 0.155744 | 0.0000408904 |
17031062400 | 0.097766 | 0.0000420051 |
17031062500 | 0.104572 | 0.0000423042 |
17031062600 | 0.136917 | 0.0000637826 |
17031062700 | 0.193846 | 0.0000784640 |
17031062800 | 0.143064 | 0.0000923569 |
17031062900 | 0.059640 | 0.0001019542 |
17031063000 | 0.096120 | 0.0000886322 |
17031063100 | 0.159480 | 0.0000577741 |
17031063200 | 0.109753 | 0.0001809348 |
17031063301 | 0.053207 | 0.0000705795 |
17031063302 | 0.123997 | 0.0001059780 |
17031063303 | 0.291742 | 0.0000336313 |
17031063400 | 0.112959 | 0.0000644079 |
17031070101 | 0.117226 | 0.0000995889 |
17031070102 | 0.048787 | 0.0000769415 |
17031070103 | 0.104559 | 0.0000437180 |
17031070200 | 0.081601 | 0.0001132915 |
17031070300 | 0.170788 | 0.0000940426 |
17031070400 | 0.110628 | 0.0000830859 |
17031070500 | 0.079831 | 0.0000915685 |
17031070600 | 0.197745 | 0.0000888497 |
17031070700 | 0.017359 | 0.0001115515 |
17031071000 | 0.064546 | 0.0001228073 |
17031071100 | 0.156652 | 0.0000874631 |
17031071200 | 0.041479 | 0.0000522006 |
17031071300 | 0.223489 | 0.0001140528 |
17031071400 | 0.066753 | 0.0001324589 |
17031071500 | 0.154570 | 0.0001647852 |
17031071600 | 0.059986 | 0.0000504877 |
17031071700 | 0.071342 | 0.0000429023 |
17031071800 | 0.063596 | 0.0000697639 |
17031080100 | 0.158860 | 0.0001710656 |
17031080201 | 0.094903 | 0.0000853969 |
17031080202 | 0.092044 | 0.0000907801 |
17031080300 | 0.116342 | 0.0001316433 |
17031080400 | 0.510526 | 0.0001114700 |
17031081000 | 0.084409 | 0.0002209008 |
17031081100 | 0.029764 | 0.0001093221 |
17031081201 | 0.168513 | 0.0001273476 |
17031081202 | 0.173969 | 0.0000772133 |
17031081300 | 0.197209 | 0.0001431166 |
17031081401 | 0.176044 | 0.0000570944 |
17031081402 | 0.335431 | 0.0001496688 |
17031081403 | 0.302367 | 0.0002235381 |
17031081500 | 0.309677 | 0.0001224538 |
17031081600 | 0.194409 | 0.0001061683 |
17031081700 | 0.205543 | 0.0001085065 |
17031081800 | 0.173014 | 0.0002717964 |
17031081900 | 0.158723 | 0.0000278947 |
17031090100 | 0.144172 | 0.0000895838 |
17031090200 | 0.172647 | 0.0001726697 |
17031090300 | 0.248675 | 0.0000352354 |
17031100100 | 0.195666 | 0.0001530673 |
17031100200 | 0.100069 | 0.0001803095 |
17031100300 | 0.155510 | 0.0001636705 |
17031100400 | 0.189935 | 0.0000909976 |
17031100500 | 0.171604 | 0.0001477113 |
17031100600 | 0.183438 | 0.0001285711 |
17031100700 | 0.175249 | 0.0001397181 |
17031110100 | 0.190245 | 0.0001470044 |
17031110200 | 0.194822 | 0.0000841462 |
17031110300 | 0.218220 | 0.0001402075 |
17031110400 | 0.263560 | 0.0001217741 |
17031110501 | 0.336194 | 0.0001426816 |
17031110502 | 0.174334 | 0.0000923841 |
17031120100 | 0.166415 | 0.0001111981 |
17031120200 | 0.112244 | 0.0001218013 |
17031120300 | 0.186702 | 0.0001815057 |
17031120400 | 0.380642 | 0.0000982567 |
17031130100 | 0.419153 | 0.0001422194 |
17031130200 | 0.288526 | 0.0000411895 |
17031130300 | 0.436002 | 0.0001442856 |
17031140100 | 0.423364 | 0.0000850978 |
17031140200 | 0.563034 | 0.0001743553 |
17031140301 | 1.179254 | 0.0000766696 |
17031140302 | 0.446225 | 0.0001036399 |
17031140400 | 0.440524 | 0.0001574989 |
17031140500 | 0.564109 | 0.0001046730 |
17031140601 | 0.683197 | 0.0000779746 |
17031140602 | 0.784657 | 0.0001305014 |
17031140701 | 0.750783 | 0.0000785727 |
17031140702 | 0.904636 | 0.0001543179 |
17031140800 | 0.368567 | 0.0001696247 |
17031150200 | 0.348090 | 0.0002048329 |
17031150300 | 0.281991 | 0.0002027394 |
17031150401 | 0.213573 | 0.0001250911 |
17031150402 | 0.258760 | 0.0000997520 |
17031150501 | 0.177293 | 0.0001011386 |
17031150502 | 0.274145 | 0.0001173425 |
17031150600 | 0.400935 | 0.0001072830 |
17031150700 | 0.502075 | 0.0001085881 |
17031150800 | 0.574212 | 0.0001237045 |
17031151001 | 0.898810 | 0.0000759627 |
17031151002 | 1.068865 | 0.0001301480 |
17031151100 | 0.848181 | 0.0001441769 |
17031151200 | 0.560806 | 0.0000973051 |
17031160100 | 0.411935 | 0.0000623960 |
17031160200 | 0.170796 | 0.0000800409 |
17031160300 | 0.128180 | 0.0000887410 |
17031160400 | 0.320564 | 0.0001229432 |
17031160501 | 0.693650 | 0.0001048633 |
17031160502 | 0.939729 | 0.0000994258 |
17031160601 | 0.360269 | 0.0000889857 |
17031160602 | 0.508201 | 0.0000975226 |
17031160700 | 0.402637 | 0.0001537198 |
17031160800 | 0.776562 | 0.0001453731 |
17031160900 | 0.204075 | 0.0000662295 |
17031161000 | 0.243186 | 0.0000578828 |
17031161100 | 0.066682 | 0.0000522278 |
17031161200 | 0.879367 | 0.0000839831 |
17031161300 | 0.650957 | 0.0000987461 |
17031170100 | 0.049673 | 0.0000524996 |
17031170200 | 0.368089 | 0.0001020630 |
17031170300 | 0.352857 | 0.0001448294 |
17031170400 | 0.194412 | 0.0001136178 |
17031170500 | 0.208456 | 0.0001490707 |
17031170600 | 0.141688 | 0.0000667189 |
17031170700 | 0.237491 | 0.0000895838 |
17031170800 | 0.284426 | 0.0001114428 |
17031170900 | 0.360067 | 0.0000528259 |
17031171000 | 0.164215 | 0.0001820223 |
17031171100 | 0.453512 | 0.0001089143 |
17031180100 | 0.551829 | 0.0001675040 |
17031190100 | 1.578152 | 0.0000666917 |
17031190200 | 1.400461 | 0.0001561395 |
17031190300 | 0.914737 | 0.0001417572 |
17031190401 | 0.839396 | 0.0001188922 |
17031190402 | 1.015999 | 0.0001460800 |
17031190601 | 1.539133 | 0.0001352865 |
17031190602 | 1.302011 | 0.0001371081 |
17031190701 | 1.481301 | 0.0000734614 |
17031190702 | 1.735694 | 0.0001371352 |
17031190800 | 1.634066 | 0.0001833817 |
17031190900 | 1.656698 | 0.0000607647 |
17031191000 | 1.623316 | 0.0000742227 |
17031191100 | 1.646773 | 0.0001843876 |
17031191200 | 1.934932 | 0.0001101921 |
17031191301 | 1.831884 | 0.0001484726 |
17031191302 | 1.661214 | 0.0001371896 |
17031200100 | 1.081045 | 0.0001027155 |
17031200200 | 1.454987 | 0.0001313442 |
17031200300 | 1.648999 | 0.0000521734 |
17031200401 | 1.559230 | 0.0000999152 |
17031200402 | 1.555732 | 0.0001195176 |
17031210100 | 0.416576 | 0.0001077996 |
17031210400 | 0.952978 | 0.0000684045 |
17031210501 | 0.683727 | 0.0000800681 |
17031210502 | 0.921475 | 0.0001175872 |
17031210601 | 0.785848 | 0.0000755549 |
17031210602 | 0.847651 | 0.0001051352 |
17031210700 | 0.717438 | 0.0001103281 |
17031210800 | 0.892132 | 0.0000313747 |
17031210900 | 0.262272 | 0.0000806118 |
17031220300 | 0.190848 | 0.0000538590 |
17031220400 | 0.137827 | 0.0000725914 |
17031220500 | 0.134631 | 0.0000648157 |
17031220601 | 0.307764 | 0.0000411623 |
17031220602 | 0.272957 | 0.0001316705 |
17031220701 | 0.978484 | 0.0000852609 |
17031220702 | 0.889181 | 0.0001048633 |
17031220901 | 0.992255 | 0.0000806662 |
17031220902 | 1.334305 | 0.0000752558 |
17031221000 | 0.658984 | 0.0000746033 |
17031221100 | 0.345292 | 0.0001291420 |
17031221200 | 0.206214 | 0.0000808565 |
17031221300 | 0.369341 | 0.0000753646 |
17031221400 | 0.390883 | 0.0000824062 |
17031221500 | 0.224523 | 0.0000733527 |
17031221600 | 0.100954 | 0.0000868106 |
17031222200 | 0.082553 | 0.0000607103 |
17031222500 | 0.501108 | 0.0000452949 |
17031222600 | 0.143387 | 0.0000440986 |
17031222700 | 0.640414 | 0.0000670179 |
17031222800 | 0.859848 | 0.0000270519 |
17031222900 | 1.107261 | 0.0000271334 |
17031230100 | 0.588485 | 0.0000436364 |
17031230200 | 0.844065 | 0.0000606288 |
17031230300 | 1.306469 | 0.0000263178 |
17031230400 | 1.466176 | 0.0000561428 |
17031230500 | 1.718902 | 0.0000904538 |
17031230600 | 1.571636 | 0.0001872152 |
17031230700 | 1.739633 | 0.0001671506 |
17031230800 | 1.497948 | 0.0000334954 |
17031230900 | 0.840743 | 0.0001273476 |
17031231100 | 1.103528 | 0.0000324079 |
17031231200 | 1.231400 | 0.0001714734 |
17031231500 | 1.382158 | 0.0001511098 |
17031240200 | 0.130252 | 0.0000426577 |
17031240300 | 0.087133 | 0.0000323807 |
17031240500 | 0.138478 | 0.0000645438 |
17031240600 | 0.201701 | 0.0000459746 |
17031240700 | 0.710352 | 0.0000499712 |
17031240800 | 0.360162 | 0.0000360510 |
17031240900 | 0.509102 | 0.0000260187 |
17031241000 | 0.509342 | 0.0000557078 |
17031241100 | 0.264561 | 0.0001002142 |
17031241200 | 0.097041 | 0.0000480952 |
17031241300 | 0.011272 | 0.0000522278 |
17031241400 | 0.037864 | 0.0001473307 |
17031241500 | 0.108373 | 0.0000726730 |
17031241600 | 0.146500 | 0.0000920035 |
17031242000 | 0.044658 | 0.0001261514 |
17031242100 | 0.143504 | 0.0001026339 |
17031242200 | 0.090228 | 0.0000961360 |
17031242300 | 0.161193 | 0.0000913782 |
17031242400 | 0.164567 | 0.0000714767 |
17031242500 | 0.227344 | 0.0000912694 |
17031242600 | 0.233251 | 0.0001413222 |
17031242700 | 0.398295 | 0.0000449958 |
17031242800 | 0.230669 | 0.0000434189 |
17031242900 | 0.072425 | 0.0000471708 |
17031243000 | 0.155017 | 0.0000579100 |
17031243100 | 0.210157 | 0.0000599219 |
17031243200 | 0.203688 | 0.0000572847 |
17031243300 | 0.129022 | 0.0000652779 |
17031243400 | 0.167937 | 0.0000744946 |
17031243500 | 0.024870 | 0.0000953204 |
17031250200 | 1.174996 | 0.0000774308 |
17031250300 | 1.262158 | 0.0001380596 |
17031250400 | 1.182831 | 0.0001284895 |
17031250500 | 0.205720 | 0.0001902874 |
17031250600 | 1.365514 | 0.0001156025 |
17031250700 | 1.372293 | 0.0001364556 |
17031250800 | 1.503462 | 0.0000710689 |
17031251000 | 1.262478 | 0.0000277859 |
17031251100 | 1.376526 | 0.0001308005 |
17031251200 | 1.292767 | 0.0001035039 |
17031251300 | 1.284640 | 0.0001084249 |
17031251400 | 0.961884 | 0.0001073918 |
17031251500 | 1.464381 | 0.0001166628 |
17031251600 | 1.503404 | 0.0001153306 |
17031251700 | 1.227940 | 0.0000321360 |
17031251800 | 1.479856 | 0.0001406425 |
17031251900 | 1.486075 | 0.0001258251 |
17031252000 | 1.644921 | 0.0001416756 |
17031252101 | 1.669782 | 0.0000345285 |
17031252102 | 1.470914 | 0.0001866170 |
17031252201 | 1.381572 | 0.0000719389 |
17031252202 | 1.543177 | 0.0001122040 |
17031260100 | 1.312760 | 0.0000322447 |
17031260200 | 1.723421 | 0.0000261003 |
17031260300 | 1.488362 | 0.0000453492 |
17031260400 | 1.747750 | 0.0000319185 |
17031260500 | 1.728129 | 0.0000414614 |
17031260600 | 1.685366 | 0.0000548650 |
17031260700 | 1.650876 | 0.0000444249 |
17031260800 | 1.529423 | 0.0000639729 |
17031260900 | 1.226196 | 0.0000391504 |
17031261000 | 1.602189 | 0.0000600850 |
17031270500 | 1.616259 | 0.0000345557 |
17031271200 | 1.399280 | 0.0000345557 |
17031271300 | 1.680717 | 0.0000301785 |
17031271400 | 1.424368 | 0.0000307766 |
17031271500 | 1.535804 | 0.0000402923 |
17031271800 | 1.732721 | 0.0000198471 |
17031280100 | 0.179182 | 0.0001710928 |
17031280400 | 1.062976 | 0.0000429567 |
17031280800 | 1.254455 | 0.0000212337 |
17031280900 | 1.214551 | 0.0000241971 |
17031281900 | 0.629821 | 0.0001641055 |
17031282700 | 0.511176 | 0.0000605472 |
17031282800 | 0.349963 | 0.0000425489 |
17031283100 | 0.656790 | 0.0000844453 |
17031283200 | 0.333355 | 0.0000421139 |
17031283800 | 0.210654 | 0.0000997248 |
17031290900 | 1.797054 | 0.0001048633 |
17031291200 | 1.578480 | 0.0000577469 |
17031291600 | 1.024175 | 0.0000256925 |
17031292200 | 1.317868 | 0.0000681326 |
17031292400 | 1.587600 | 0.0000543756 |
17031292500 | 1.424507 | 0.0000900732 |
17031300500 | 1.888550 | 0.0000791165 |
17031300600 | 1.313947 | 0.0000818896 |
17031300700 | 2.002344 | 0.0001316161 |
17031300800 | 2.143834 | 0.0001073374 |
17031300900 | 1.917506 | 0.0001148141 |
17031301100 | 1.594700 | 0.0000596500 |
17031301200 | 1.701667 | 0.0001197079 |
17031301600 | 1.965281 | 0.0001153306 |
17031301701 | 2.154395 | 0.0001029058 |
17031301702 | 2.098414 | 0.0001256348 |
17031301801 | 1.943940 | 0.0000966254 |
17031301802 | 2.043790 | 0.0000928191 |
17031301803 | 2.018604 | 0.0001202516 |
17031310200 | 0.673712 | 0.0000469805 |
17031310300 | 0.768670 | 0.0000500527 |
17031310400 | 0.510719 | 0.0000340391 |
17031310500 | 1.271623 | 0.0000405370 |
17031310600 | 0.785605 | 0.0001224266 |
17031310700 | 0.942170 | 0.0000399117 |
17031310800 | 1.345778 | 0.0001182125 |
17031310900 | 1.485219 | 0.0001387937 |
17031320100 | 0.241799 | 0.0003581992 |
17031320400 | 0.127257 | 0.0000817537 |
17031320600 | 0.221514 | 0.0001364827 |
17031330100 | 0.086749 | 0.0005273889 |
17031330200 | 0.313972 | 0.0000952660 |
17031340300 | 2.154673 | 0.0000507868 |
17031340400 | 2.056179 | 0.0000529890 |
17031340500 | 0.660107 | 0.0000429295 |
17031340600 | 1.747029 | 0.0000262906 |
17031350100 | 1.359950 | 0.0000610366 |
17031350400 | 1.783903 | 0.0000538046 |
17031351000 | 1.205925 | 0.0000840919 |
17031351100 | 1.656149 | 0.0000648429 |
17031351400 | 1.341655 | 0.0000496993 |
17031351500 | 0.704494 | 0.0000191946 |
17031360200 | 1.476928 | 0.0000401564 |
17031380100 | 1.435855 | 0.0000495905 |
17031380200 | 1.614559 | 0.0000411079 |
17031380500 | 1.819540 | 0.0000232728 |
17031380700 | 1.451367 | 0.0000356432 |
17031381200 | 1.625536 | 0.0000474155 |
17031381400 | 1.665415 | 0.0000384707 |
17031381500 | 1.585543 | 0.0000091079 |
17031381800 | 1.289665 | 0.0000337944 |
17031381900 | 1.389303 | 0.0000282753 |
17031390100 | 1.289169 | 0.0000399389 |
17031390200 | 0.906173 | 0.0000526356 |
17031390300 | 1.116178 | 0.0000794699 |
17031390400 | 1.084653 | 0.0000688123 |
17031390500 | 0.561565 | 0.0000419508 |
17031390600 | 0.213537 | 0.0000434189 |
17031390700 | 0.754197 | 0.0001413765 |
17031400300 | 1.531362 | 0.0000361326 |
17031400400 | 1.748270 | 0.0000563331 |
17031400500 | 1.724651 | 0.0000563603 |
17031400800 | 1.685463 | 0.0000641632 |
17031410100 | 0.266239 | 0.0000511946 |
17031410200 | 0.268931 | 0.0000387154 |
17031410500 | 0.299295 | 0.0000667732 |
17031410600 | 0.117368 | 0.0000641088 |
17031410700 | 0.154895 | 0.0000567137 |
17031410800 | 0.255647 | 0.0000729992 |
17031410900 | 0.098210 | 0.0000852337 |
17031411000 | 0.186899 | 0.0000929007 |
17031411100 | 0.178514 | 0.0000595957 |
17031411200 | 0.220223 | 0.0000437452 |
17031420100 | 1.473059 | 0.0000399389 |
17031420200 | 0.648046 | 0.0000460561 |
17031420300 | 0.334468 | 0.0000734342 |
17031420400 | 0.682735 | 0.0000303960 |
17031420500 | 1.538740 | 0.0000471708 |
17031420600 | 1.518919 | 0.0000496993 |
17031420700 | 1.655455 | 0.0000709330 |
17031420800 | 1.576662 | 0.0000609007 |
17031421200 | 1.666823 | 0.0000298250 |
17031430101 | 1.656560 | 0.0000869738 |
17031430102 | 1.538955 | 0.0000829500 |
17031430200 | 1.479544 | 0.0001297945 |
17031430300 | 1.664997 | 0.0000665557 |
17031430400 | 1.570142 | 0.0000740596 |
17031430500 | 1.642926 | 0.0000937163 |
17031430600 | 1.514344 | 0.0000579916 |
17031430700 | 1.558935 | 0.0000718845 |
17031430800 | 1.647920 | 0.0000526628 |
17031430900 | 1.797195 | 0.0000400204 |
17031431200 | 1.724620 | 0.0000722108 |
17031431301 | 1.558345 | 0.0000871913 |
17031431302 | 1.510984 | 0.0001174513 |
17031431400 | 1.351015 | 0.0001836264 |
17031440101 | 1.765823 | 0.0001086424 |
17031440102 | 1.374858 | 0.0000938523 |
17031440201 | 1.642911 | 0.0001382228 |
17031440202 | 1.601909 | 0.0000816450 |
17031440300 | 1.685967 | 0.0001253901 |
17031440600 | 1.749311 | 0.0000483127 |
17031440700 | 1.686358 | 0.0000398029 |
17031440800 | 1.604868 | 0.0000494818 |
17031440900 | 1.815122 | 0.0000626951 |
17031450300 | 1.734897 | 0.0000987189 |
17031460100 | 1.348770 | 0.0000946951 |
17031460200 | 0.946538 | 0.0000670995 |
17031460301 | 1.241164 | 0.0000984470 |
17031460302 | 1.212429 | 0.0000897469 |
17031460400 | 1.748115 | 0.0000897741 |
17031460500 | 1.755648 | 0.0001599186 |
17031460600 | 1.327253 | 0.0000324350 |
17031460700 | 1.109964 | 0.0000707426 |
17031461000 | 1.025967 | 0.0000349091 |
17031470100 | 1.691958 | 0.0000538318 |
17031480100 | 1.762855 | 0.0000586713 |
17031480200 | 1.770169 | 0.0000288734 |
17031480300 | 1.609730 | 0.0000298794 |
17031480400 | 1.684188 | 0.0001475482 |
17031480500 | 1.361897 | 0.0000799049 |
17031490300 | 1.631938 | 0.0000612813 |
17031490400 | 1.819540 | 0.0000201733 |
17031490500 | 1.548872 | 0.0000542125 |
17031490600 | 1.379457 | 0.0000398029 |
17031490700 | 1.791712 | 0.0000755005 |
17031490800 | 1.689545 | 0.0001078812 |
17031490901 | 1.713474 | 0.0000884963 |
17031490902 | 1.718261 | 0.0001131828 |
17031491000 | 1.681847 | 0.0000907257 |
17031491100 | 1.556311 | 0.0001141344 |
17031491200 | 1.430663 | 0.0000490740 |
17031491300 | 1.783729 | 0.0000625319 |
17031491400 | 1.668540 | 0.0000893119 |
17031500100 | 1.667205 | 0.0000852609 |
17031500200 | 1.679228 | 0.0000542940 |
17031500300 | 0.241582 | 0.0000402108 |
17031510100 | 1.404958 | 0.0000903179 |
17031510200 | 1.241916 | 0.0001087784 |
17031510300 | 1.754927 | 0.0001309636 |
17031520100 | 1.632023 | 0.0000544028 |
17031520200 | 1.311992 | 0.0000864028 |
17031520300 | 1.588064 | 0.0001604624 |
17031520400 | 1.596768 | 0.0001227529 |
17031520500 | 1.129494 | 0.0001421922 |
17031520600 | 1.301894 | 0.0000775396 |
17031530100 | 1.368965 | 0.0000594325 |
17031530200 | 1.767321 | 0.0001193544 |
17031530300 | 1.760021 | 0.0001058693 |
17031530400 | 1.587796 | 0.0000587256 |
17031530501 | 1.603953 | 0.0001110350 |
17031530502 | 1.729752 | 0.0000393679 |
17031530503 | 1.767611 | 0.0001641327 |
17031530600 | 1.753621 | 0.0000629669 |
17031540101 | 1.545015 | 0.0001115787 |
17031540102 | 1.678342 | 0.0000884963 |
17031550100 | 0.752588 | 0.0001751710 |
17031550200 | 0.772265 | 0.0000713408 |
17031560100 | 1.098017 | 0.0000408089 |
17031560200 | 1.150420 | 0.0000442345 |
17031560300 | 1.026499 | 0.0000885507 |
17031560400 | 1.061433 | 0.0000491283 |
17031560700 | 0.778911 | 0.0001020358 |
17031560800 | 0.474575 | 0.0001582602 |
17031560900 | 0.385848 | 0.0001451285 |
17031561000 | 0.440363 | 0.0001681837 |
17031561100 | 0.646696 | 0.0001536111 |
17031570100 | 1.231374 | 0.0000343110 |
17031570200 | 1.293407 | 0.0000607919 |
17031570300 | 1.281877 | 0.0001605711 |
17031570400 | 1.506499 | 0.0000445880 |
17031570500 | 1.315599 | 0.0000718030 |
17031580100 | 1.529219 | 0.0000710417 |
17031580200 | 1.591372 | 0.0000880069 |
17031580300 | 1.578081 | 0.0000681054 |
17031580400 | 1.538766 | 0.0001329755 |
17031580501 | 1.489951 | 0.0001350690 |
17031580502 | 1.536444 | 0.0001424641 |
17031580600 | 1.413259 | 0.0001407784 |
17031580700 | 1.496763 | 0.0001589942 |
17031580800 | 2.084480 | 0.0000611454 |
17031590500 | 1.010424 | 0.0000497809 |
17031590600 | 1.023325 | 0.0000901547 |
17031590700 | 1.356130 | 0.0000889857 |
17031600400 | 1.358593 | 0.0001138625 |
17031600600 | 1.181220 | 0.0000854784 |
17031600700 | 0.637680 | 0.0000758540 |
17031600900 | 0.328493 | 0.0000953476 |
17031610300 | 1.747858 | 0.0001577980 |
17031610400 | 1.943204 | 0.0000530434 |
17031610800 | 0.259717 | 0.0000400204 |
17031611000 | 1.017179 | 0.0000223756 |
17031611100 | 1.326506 | 0.0000689211 |
17031611200 | 1.231385 | 0.0000634291 |
17031611300 | 1.681738 | 0.0000720477 |
17031611400 | 1.936655 | 0.0000761802 |
17031611500 | 1.564883 | 0.0000872728 |
17031611600 | 1.255287 | 0.0000424673 |
17031611700 | 1.435880 | 0.0000547018 |
17031611800 | 1.213152 | 0.0000610638 |
17031611900 | 1.251167 | 0.0000445608 |
17031612000 | 1.408585 | 0.0000366220 |
17031612100 | 1.465049 | 0.0000277859 |
17031620100 | 1.608268 | 0.0001300936 |
17031620200 | 1.069848 | 0.0000581275 |
17031620300 | 1.241916 | 0.0002119017 |
17031620400 | 1.596318 | 0.0001191641 |
17031630100 | 1.329863 | 0.0000240068 |
17031630200 | 1.724756 | 0.0000496177 |
17031630300 | 1.920123 | 0.0001490707 |
17031630400 | 1.923172 | 0.0001734310 |
17031630500 | 1.928376 | 0.0001607614 |
17031630800 | 1.817500 | 0.0001843604 |
17031630900 | 1.826526 | 0.0001399084 |
17031640100 | 1.002347 | 0.0000406729 |
17031640300 | 0.605510 | 0.0001789229 |
17031640400 | 0.326094 | 0.0000915685 |
17031640500 | 0.487381 | 0.0001057605 |
17031640600 | 0.670514 | 0.0001138353 |
17031640700 | 0.887429 | 0.0000920307 |
17031640800 | 1.235302 | 0.0000471165 |
17031650100 | 1.334553 | 0.0001190825 |
17031650200 | 1.541755 | 0.0001929790 |
17031650301 | 1.323282 | 0.0001330571 |
17031650302 | 1.895655 | 0.0001140528 |
17031650400 | 1.723665 | 0.0001807445 |
17031650500 | 1.118033 | 0.0001243842 |
17031660301 | 1.380687 | 0.0000377095 |
17031660302 | 1.418382 | 0.0001341990 |
17031660400 | 1.802274 | 0.0001577980 |
17031660500 | 1.594297 | 0.0001210944 |
17031660600 | 1.196161 | 0.0001514360 |
17031660700 | 1.471950 | 0.0000401564 |
17031660800 | 1.124704 | 0.0001299033 |
17031660900 | 1.285101 | 0.0001166628 |
17031661000 | 1.405639 | 0.0001441225 |
17031661100 | 1.156901 | 0.0001866442 |
17031670100 | 1.261284 | 0.0000272150 |
17031670200 | 1.460571 | 0.0000250943 |
17031670300 | 1.172261 | 0.0000285472 |
17031670400 | 1.376950 | 0.0000459202 |
17031670500 | 1.295938 | 0.0000247681 |
17031670600 | 1.430582 | 0.0000265081 |
17031670700 | 1.358495 | 0.0000302600 |
17031670800 | 1.695666 | 0.0000275956 |
17031670900 | 1.313915 | 0.0000337129 |
17031671100 | 1.728203 | 0.0000200102 |
17031671200 | 1.658899 | 0.0000277044 |
17031671300 | 1.588546 | 0.0000547018 |
17031671400 | 1.577283 | 0.0000311844 |
17031671500 | 1.390068 | 0.0000596228 |
17031671600 | 1.455720 | 0.0000445608 |
17031671800 | 1.546822 | 0.0000370842 |
17031671900 | 1.335231 | 0.0000305863 |
17031672000 | 1.674651 | 0.0000940698 |
17031680500 | 1.477184 | 0.0000335769 |
17031680600 | 1.790023 | 0.0000318369 |
17031680900 | 1.658844 | 0.0000897741 |
17031681000 | 1.725233 | 0.0000733799 |
17031681100 | 1.534028 | 0.0000702533 |
17031681200 | 1.579541 | 0.0000660935 |
17031681300 | 1.712802 | 0.0000657401 |
17031681400 | 1.707287 | 0.0000649245 |
17031690300 | 1.581179 | 0.0000657129 |
17031690400 | 1.712156 | 0.0000793068 |
17031690500 | 1.819540 | 0.0000171827 |
17031690900 | 1.750907 | 0.0001120409 |
17031691000 | 1.771802 | 0.0000613357 |
17031691100 | 1.631290 | 0.0000750111 |
17031691200 | 1.779094 | 0.0000723739 |
17031691300 | 1.494123 | 0.0000656313 |
17031691400 | 1.766191 | 0.0000838200 |
17031691500 | 1.567682 | 0.0000535056 |
17031700100 | 1.240932 | 0.0000962992 |
17031700200 | 1.151884 | 0.0001750078 |
17031700301 | 1.089174 | 0.0001757419 |
17031700302 | 0.828861 | 0.0001583689 |
17031700401 | 1.021317 | 0.0001666068 |
17031700402 | 0.865961 | 0.0001219101 |
17031700501 | 1.382655 | 0.0001648940 |
17031700502 | 1.350984 | 0.0000919219 |
17031710100 | 1.670070 | 0.0000338488 |
17031710200 | 1.577617 | 0.0001173153 |
17031710300 | 1.534069 | 0.0000408361 |
17031710400 | 1.612375 | 0.0001515992 |
17031710500 | 1.665664 | 0.0001159831 |
17031710600 | 1.627993 | 0.0000456483 |
17031710700 | 1.765646 | 0.0000867834 |
17031710800 | 1.767667 | 0.0001268583 |
17031710900 | 1.591405 | 0.0000530706 |
17031711000 | 1.404939 | 0.0000895294 |
17031711100 | 1.709729 | 0.0000637010 |
17031711200 | 1.738009 | 0.0001309364 |
17031711300 | 1.523826 | 0.0000430383 |
17031711400 | 1.672522 | 0.0000690570 |
17031711500 | 1.791023 | 0.0000676704 |
17031720100 | 0.128178 | 0.0000893391 |
17031720200 | 0.409605 | 0.0000993442 |
17031720300 | 0.088799 | 0.0001024980 |
17031720400 | 0.139713 | 0.0000519559 |
17031720500 | 0.156670 | 0.0000519015 |
17031720600 | 0.115284 | 0.0000477961 |
17031720700 | 0.514918 | 0.0000817537 |
17031730100 | 1.752750 | 0.0000731352 |
17031730201 | 1.518081 | 0.0001430622 |
17031730202 | 1.668801 | 0.0000836297 |
17031730300 | 1.767948 | 0.0000297434 |
17031730400 | 1.579816 | 0.0001096756 |
17031730500 | 1.779691 | 0.0001121225 |
17031730600 | 1.771642 | 0.0001018183 |
17031730700 | 1.712138 | 0.0000647341 |
17031740100 | 0.198819 | 0.0000836568 |
17031740200 | 0.152592 | 0.0001785694 |
17031740300 | 0.145948 | 0.0001324318 |
17031740400 | 0.015678 | 0.0001203060 |
17031750100 | 1.637792 | 0.0001002686 |
17031750200 | 0.398328 | 0.0000753102 |
17031750300 | 0.118261 | 0.0000675889 |
17031750400 | 0.078244 | 0.0000836025 |
17031750500 | 0.873485 | 0.0001419747 |
17031750600 | 1.681858 | 0.0000880613 |
17031760801 | 0.363123 | 0.0001189194 |
17031760802 | 0.212492 | 0.0000694104 |
17031760803 | 0.127694 | 0.0001545082 |
17031770201 | 0.121187 | 0.0001612236 |
17031770202 | 0.186663 | 0.0001287342 |
17031770300 | 0.117881 | 0.0001845508 |
17031770400 | 0.183757 | 0.0001194904 |
17031770500 | 1.501813 | 0.0001089143 |
17031770601 | 0.403844 | 0.0000867291 |
17031770602 | 0.679436 | 0.0001400172 |
17031770700 | 0.182004 | 0.0000620154 |
17031770800 | 0.169570 | 0.0001426816 |
17031770901 | 0.189308 | 0.0001337096 |
17031770902 | 0.185413 | 0.0000881156 |
17031800100 | 0.258819 | 0.0000614716 |
17031800200 | 0.113700 | 0.0001777810 |
17031800300 | 0.237859 | 0.0000885235 |
17031800400 | 0.242187 | 0.0000941242 |
17031800500 | 0.221084 | 0.0001440681 |
17031800600 | 0.248396 | 0.0000634563 |
17031800700 | 0.239320 | 0.0001262329 |
17031800800 | 0.133914 | 0.0000617979 |
17031800900 | 0.407685 | 0.0001158744 |
17031801000 | 0.331240 | 0.0001366459 |
17031801100 | 0.245614 | 0.0001293867 |
17031801200 | 0.203169 | 0.0000957554 |
17031801300 | 0.213170 | 0.0001121768 |
17031801400 | 0.238244 | 0.0000831403 |
17031801500 | 0.144969 | 0.0001635074 |
17031801601 | 0.269467 | 0.0001197622 |
17031801603 | 0.286539 | 0.0001092949 |
17031801605 | 0.347285 | 0.0001477657 |
17031801606 | 0.314803 | 0.0001633171 |
17031801607 | 0.511786 | 0.0001403978 |
17031801608 | 0.525584 | 0.0001909671 |
17031801701 | 0.322400 | 0.0001048361 |
17031801702 | 0.217895 | 0.0001232967 |
17031801800 | 0.262563 | 0.0001546442 |
17031801901 | 0.170355 | 0.0001151131 |
17031801902 | 0.272479 | 0.0000917044 |
17031802002 | 0.138304 | 0.0001465966 |
17031802003 | 0.296292 | 0.0000689211 |
17031802004 | 0.346476 | 0.0001357759 |
17031802100 | 0.248837 | 0.0000890400 |
17031802200 | 0.193044 | 0.0001288702 |
17031802300 | 0.261767 | 0.0001450197 |
17031802402 | 0.285448 | 0.0001576892 |
17031802403 | 0.170733 | 0.0000358879 |
17031802404 | 0.507427 | 0.0002024403 |
17031802503 | 0.486674 | 0.0001592389 |
17031802504 | 0.478800 | 0.0001767751 |
17031802505 | 0.681510 | 0.0001764760 |
17031802506 | 0.621886 | 0.0000653051 |
17031802605 | 0.338463 | 0.0001867802 |
17031802607 | 0.158145 | 0.0000337672 |
17031802608 | 0.159303 | 0.0001720444 |
17031802609 | 0.619750 | 0.0001694343 |
17031802610 | 0.272034 | 0.0000439355 |
17031802701 | 0.292142 | 0.0001850130 |
17031802702 | 0.369076 | 0.0001259339 |
17031802801 | 0.155590 | 0.0001291420 |
17031802802 | 0.079929 | 0.0001769926 |
17031802900 | 0.199833 | 0.0001597555 |
17031803005 | 0.223700 | 0.0000672898 |
17031803007 | 0.166584 | 0.0001326221 |
17031803008 | 0.142870 | 0.0001211488 |
17031803010 | 0.164080 | 0.0001460257 |
17031803012 | 0.131980 | 0.0000549465 |
17031803013 | 0.158039 | 0.0001379237 |
17031803014 | 0.183158 | 0.0000949942 |
17031803015 | 0.047257 | 0.0001187563 |
17031803016 | 1.156859 | 0.0000700901 |
17031803017 | 0.220300 | 0.0001601089 |
17031803100 | 0.222434 | 0.0000908616 |
17031803200 | 0.171727 | 0.0001443672 |
17031803300 | 0.192946 | 0.0001523332 |
17031803400 | 0.229050 | 0.0001692168 |
17031803500 | 0.239176 | 0.0001559220 |
17031803603 | 0.385712 | 0.0001835448 |
17031803604 | 0.145270 | 0.0001124487 |
17031803605 | 0.088828 | 0.0001948821 |
17031803606 | 0.979957 | 0.0002462942 |
17031803607 | 0.172232 | 0.0001306102 |
17031803608 | 0.116333 | 0.0001862636 |
17031803610 | 0.135378 | 0.0001908311 |
17031803611 | 0.536231 | 0.0001521157 |
17031803612 | 0.762566 | 0.0000932541 |
17031803701 | 0.177621 | 0.0000738692 |
17031803702 | 0.193141 | 0.0001571998 |
17031803800 | 0.114175 | 0.0001212304 |
17031803901 | 0.171611 | 0.0000985558 |
17031803902 | 0.201980 | 0.0000897197 |
17031804000 | 0.141801 | 0.0001218285 |
17031804102 | 0.228774 | 0.0001946918 |
17031804104 | 0.406099 | 0.0001251998 |
17031804105 | 0.215702 | 0.0001024980 |
17031804106 | 0.386626 | 0.0001809076 |
17031804108 | 0.771295 | 0.0001021989 |
17031804109 | 0.100462 | 0.0000724283 |
17031804201 | 0.341395 | 0.0002283231 |
17031804202 | 0.291860 | 0.0001948278 |
17031804305 | 0.282883 | 0.0001886017 |
17031804306 | 0.547454 | 0.0001549976 |
17031804308 | 0.450628 | 0.0001860461 |
17031804309 | 0.446436 | 0.0000818896 |
17031804310 | 0.385480 | 0.0002392254 |
17031804311 | 0.425956 | 0.0002209008 |
17031804403 | 0.357806 | 0.0001772372 |
17031804404 | 0.935466 | 0.0001561667 |
17031804405 | 0.939296 | 0.0000909976 |
17031804406 | 0.704160 | 0.0001789501 |
17031804505 | 0.072392 | 0.0000909976 |
17031804506 | 0.258652 | 0.0001355040 |
17031804507 | 0.295210 | 0.0003022195 |
17031804508 | 0.766249 | 0.0000610638 |
17031804509 | 0.818256 | 0.0001634802 |
17031804510 | 1.191297 | 0.0001698422 |
17031804511 | 0.792922 | 0.0000675073 |
17031804603 | 0.502783 | 0.0001633987 |
17031804606 | 0.191344 | 0.0001825932 |
17031804607 | 0.247135 | 0.0001862908 |
17031804608 | 0.361846 | 0.0000893119 |
17031804609 | 0.767735 | 0.0001460800 |
17031804610 | 0.306789 | 0.0000607647 |
17031804611 | 0.207744 | 0.0001179135 |
17031804701 | 0.423224 | 0.0001624471 |
17031804705 | 0.306141 | 0.0001162278 |
17031804706 | 0.215814 | 0.0000630485 |
17031804709 | 0.392545 | 0.0001592933 |
17031804710 | 0.141044 | 0.0000985830 |
17031804711 | 0.568897 | 0.0002092645 |
17031804712 | 0.189668 | 0.0001384674 |
17031804713 | 0.477726 | 0.0001575261 |
17031804714 | 0.268324 | 0.0000821887 |
17031804715 | 0.767606 | 0.0000846084 |
17031804716 | 0.576085 | 0.0001225898 |
17031804803 | 0.232193 | 0.0001603808 |
17031804804 | 0.402366 | 0.0001673953 |
17031804805 | 0.227253 | 0.0001699781 |
17031804806 | 0.250810 | 0.0001010570 |
17031804807 | 0.187147 | 0.0001440138 |
17031804808 | 0.162917 | 0.0000684589 |
17031804809 | 0.205926 | 0.0001112797 |
17031804810 | 0.219976 | 0.0001799560 |
17031804901 | 0.142729 | 0.0001678303 |
17031804902 | 0.176614 | 0.0001415669 |
17031805001 | 0.218503 | 0.0001332202 |
17031805002 | 0.274491 | 0.0001796570 |
17031805105 | 0.541307 | 0.0001933596 |
17031805106 | 0.201043 | 0.0000799321 |
17031805107 | 0.459619 | 0.0001657640 |
17031805108 | 0.239655 | 0.0001737572 |
17031805109 | 0.131921 | 0.0001131556 |
17031805110 | 0.236664 | 0.0001191913 |
17031805111 | 0.447828 | 0.0001965950 |
17031805112 | 0.499822 | 0.0000880885 |
17031805201 | 0.250528 | 0.0001065218 |
17031805202 | 0.241115 | 0.0001151131 |
17031805301 | 0.540218 | 0.0000802584 |
17031805302 | 0.632327 | 0.0000945048 |
17031805401 | 0.149964 | 0.0001003230 |
17031805402 | 0.181257 | 0.0001335193 |
17031805501 | 0.096051 | 0.0000951029 |
17031805502 | 0.238838 | 0.0001046458 |
17031805600 | 0.221510 | 0.0001212576 |
17031805701 | 0.219414 | 0.0001349874 |
17031805702 | 0.239063 | 0.0000517656 |
17031805801 | 0.222624 | 0.0000619066 |
17031805802 | 0.201698 | 0.0001276195 |
17031805901 | 0.189229 | 0.0001086424 |
17031805902 | 0.219260 | 0.0001633171 |
17031806001 | 0.620650 | 0.0001439050 |
17031806002 | 0.444249 | 0.0001940937 |
17031806003 | 0.970195 | 0.0002196502 |
17031806004 | 0.419935 | 0.0001929790 |
17031806102 | 0.166916 | 0.0001010842 |
17031806103 | 0.206996 | 0.0001260154 |
17031806104 | 0.340707 | 0.0001092949 |
17031806201 | 0.238279 | 0.0001310724 |
17031806202 | 0.075615 | 0.0001270758 |
17031806300 | 0.156845 | 0.0001203060 |
17031806400 | 0.193066 | 0.0000672082 |
17031806501 | 0.334246 | 0.0000628582 |
17031806502 | 0.254775 | 0.0001181310 |
17031806600 | 0.272546 | 0.0000938251 |
17031806700 | 0.148781 | 0.0001043468 |
17031806801 | 0.415520 | 0.0001065762 |
17031806802 | 0.282341 | 0.0000809653 |
17031806900 | 0.477401 | 0.0001278914 |
17031807000 | 0.511931 | 0.0001512185 |
17031807100 | 0.031591 | 0.0000926016 |
17031807200 | 0.287515 | 0.0001403978 |
17031807300 | 0.507745 | 0.0001909127 |
17031807400 | 0.287787 | 0.0001799016 |
17031807500 | 0.528551 | 0.0000885235 |
17031807600 | 0.616878 | 0.0001610605 |
17031807700 | 0.321895 | 0.0001402075 |
17031807800 | 0.384760 | 0.0000687851 |
17031807900 | 0.403276 | 0.0001108990 |
17031808001 | 0.646725 | 0.0000950757 |
17031808002 | 0.298622 | 0.0001144062 |
17031808100 | 0.117642 | 0.0000989908 |
17031808200 | 0.443144 | 0.0001439322 |
17031808301 | 0.328357 | 0.0001552423 |
17031808302 | 0.543496 | 0.0001055158 |
17031808400 | 0.374923 | 0.0001101378 |
17031808500 | 0.406008 | 0.0001074190 |
17031808600 | 0.209802 | 0.0000555719 |
17031808702 | 0.211802 | 0.0001368090 |
17031808800 | 0.149538 | 0.0001010299 |
17031808900 | 0.221062 | 0.0001116331 |
17031809000 | 0.133918 | 0.0001044011 |
17031809100 | 0.082374 | 0.0000847444 |
17031809200 | 0.771736 | 0.0001102737 |
17031809300 | 0.185259 | 0.0001172066 |
17031809400 | 0.308233 | 0.0001414853 |
17031809500 | 0.134200 | 0.0001096484 |
17031809600 | 0.229028 | 0.0000814818 |
17031809700 | 0.155101 | 0.0000944232 |
17031809800 | 0.045517 | 0.0000686764 |
17031809900 | 0.102239 | 0.0000735702 |
17031810000 | 0.096043 | 0.0001327308 |
17031810100 | 0.015175 | 0.0001106271 |
17031810200 | 0.219640 | 0.0001705762 |
17031810301 | 0.267276 | 0.0001183485 |
17031810302 | 0.041690 | 0.0000818625 |
17031810400 | 0.222750 | 0.0001456450 |
17031810501 | 0.178225 | 0.0001419747 |
17031810502 | 0.148156 | 0.0001485269 |
17031810600 | 0.169291 | 0.0001192457 |
17031810701 | 0.453132 | 0.0001348787 |
17031810702 | 0.357518 | 0.0001017367 |
17031810800 | 0.186161 | 0.0001377606 |
17031810900 | 0.209859 | 0.0001733222 |
17031811000 | 0.129346 | 0.0001080171 |
17031811100 | 0.320286 | 0.0001647309 |
17031811200 | 0.204771 | 0.0001328668 |
17031811301 | 0.992669 | 0.0001209857 |
17031811302 | 1.385922 | 0.0001119050 |
17031811401 | 0.404310 | 0.0001203604 |
17031811402 | 0.629539 | 0.0001114428 |
17031811500 | 0.507754 | 0.0001725066 |
17031811600 | 0.284345 | 0.0001702500 |
17031811701 | 1.137366 | 0.0001052168 |
17031811702 | 0.770296 | 0.0001430350 |
17031811800 | 0.720255 | 0.0001392559 |
17031811900 | 0.046803 | 0.0001549433 |
17031812000 | 0.130721 | 0.0001344980 |
17031812100 | 0.070618 | 0.0001212576 |
17031812200 | 0.024810 | 0.0000974954 |
17031812301 | 0.022275 | 0.0001077452 |
17031812302 | 0.004311 | 0.0000719117 |
17031812400 | 0.101758 | 0.0000829772 |
17031812500 | 0.026069 | 0.0000825965 |
17031812600 | 0.059212 | 0.0000862125 |
17031812700 | 0.020391 | 0.0000816721 |
17031812801 | 0.053590 | 0.0000844997 |
17031812802 | 0.022843 | 0.0000645710 |
17031812900 | 0.022724 | 0.0001232967 |
17031813000 | 0.018483 | 0.0001086968 |
17031813100 | 0.049675 | 0.0001274292 |
17031813200 | 0.020686 | 0.0001042108 |
17031813301 | 1.892349 | 0.0000877894 |
17031813302 | 1.787453 | 0.0000830043 |
17031813400 | 1.800272 | 0.0002067088 |
17031813500 | 1.675082 | 0.0001735125 |
17031813600 | 1.955087 | 0.0001474122 |
17031813701 | 1.845147 | 0.0001008667 |
17031813702 | 1.800560 | 0.0001057605 |
17031813801 | 2.111788 | 0.0000738692 |
17031813802 | 1.648249 | 0.0001346340 |
17031813900 | 1.539685 | 0.0001763129 |
17031814000 | 1.686923 | 0.0001243026 |
17031814100 | 1.798219 | 0.0001139984 |
17031814200 | 1.696929 | 0.0001897980 |
17031814300 | 1.860468 | 0.0001377062 |
17031814400 | 1.472442 | 0.0002189433 |
17031814500 | 1.559874 | 0.0001553783 |
17031814600 | 0.851483 | 0.0001537198 |
17031814700 | 0.970523 | 0.0001423553 |
17031814800 | 0.600949 | 0.0001603536 |
17031814900 | 0.734785 | 0.0001762857 |
17031815000 | 0.902594 | 0.0001013017 |
17031815100 | 1.259796 | 0.0001222363 |
17031815200 | 1.128737 | 0.0001804182 |
17031815300 | 0.717664 | 0.0000900732 |
17031815400 | 0.559787 | 0.0001366459 |
17031815500 | 1.163763 | 0.0002272084 |
17031815600 | 0.251409 | 0.0001333018 |
17031815701 | 0.201331 | 0.0000967342 |
17031815702 | 0.101488 | 0.0001365915 |
17031815800 | 0.177065 | 0.0000435277 |
17031815900 | 0.084678 | 0.0001296586 |
17031816000 | 0.023649 | 0.0000847172 |
17031816100 | 0.076446 | 0.0001522517 |
17031816200 | 0.472108 | 0.0001129109 |
17031816300 | 1.102932 | 0.0001336280 |
17031816401 | 1.601017 | 0.0001407240 |
17031816402 | 1.231671 | 0.0001156569 |
17031816500 | 1.379680 | 0.0001144334 |
17031816600 | 1.736909 | 0.0001268854 |
17031816700 | 1.168046 | 0.0000754733 |
17031816800 | 0.369129 | 0.0001409143 |
17031816900 | 1.080910 | 0.0001626374 |
17031817000 | 0.979188 | 0.0001349330 |
17031817101 | 1.315343 | 0.0001265864 |
17031817102 | 1.440769 | 0.0000836568 |
17031817200 | 1.284462 | 0.0001137537 |
17031817300 | 1.193250 | 0.0000692745 |
17031817400 | 1.027136 | 0.0001086152 |
17031817500 | 1.179892 | 0.0000954020 |
17031817600 | 1.246520 | 0.0001073646 |
17031817700 | 1.243167 | 0.0001401803 |
17031817900 | 1.015817 | 0.0001537198 |
17031818000 | 0.424663 | 0.0001071743 |
17031818100 | 0.097282 | 0.0000617979 |
17031818200 | 0.240203 | 0.0001211216 |
17031818300 | 0.699977 | 0.0001621208 |
17031818401 | 0.152061 | 0.0000916772 |
17031818402 | 0.033329 | 0.0000781649 |
17031818500 | 0.033351 | 0.0001467597 |
17031818600 | 0.046146 | 0.0001342805 |
17031818700 | 0.107362 | 0.0001011930 |
17031818800 | 0.128189 | 0.0001390928 |
17031818900 | 0.087066 | 0.0001150316 |
17031819000 | 0.276219 | 0.0001241123 |
17031819100 | 0.445842 | 0.0001108990 |
17031819200 | 0.633825 | 0.0001717181 |
17031819300 | 0.213985 | 0.0000730264 |
17031819400 | 0.173750 | 0.0001451828 |
17031819500 | 0.034596 | 0.0000889857 |
17031819600 | 0.251924 | 0.0001008667 |
17031819700 | 0.221000 | 0.0001489891 |
17031819801 | 0.180481 | 0.0001481735 |
17031819802 | 0.233534 | 0.0000696823 |
17031819900 | 0.242176 | 0.0000896654 |
17031820000 | 0.226655 | 0.0000591063 |
17031820101 | 0.152713 | 0.0001934412 |
17031820103 | 0.163126 | 0.0001138625 |
17031820104 | 0.130348 | 0.0001109534 |
17031820201 | 0.135834 | 0.0001928702 |
17031820202 | 0.278374 | 0.0000850434 |
17031820300 | 1.102122 | 0.0001499679 |
17031820400 | 1.369813 | 0.0001526595 |
17031820501 | 0.140699 | 0.0001597283 |
17031820502 | 0.106122 | 0.0001406968 |
17031820603 | 0.199107 | 0.0001578252 |
17031820604 | 0.211915 | 0.0001059237 |
17031820605 | 0.464233 | 0.0001246289 |
17031820606 | 0.104382 | 0.0001032049 |
17031820700 | 0.858736 | 0.0001771285 |
17031820800 | 0.774462 | 0.0001045643 |
17031820901 | 0.322704 | 0.0001451828 |
17031820902 | 0.395617 | 0.0001374615 |
17031821001 | 0.150452 | 0.0001278370 |
17031821002 | 0.316324 | 0.0001466238 |
17031821101 | 0.257984 | 0.0001250367 |
17031821102 | 0.292938 | 0.0001156025 |
17031821200 | 1.003164 | 0.0001697062 |
17031821300 | 0.847727 | 0.0001471675 |
17031821401 | 1.410226 | 0.0001018727 |
17031821402 | 1.634488 | 0.0000792796 |
17031821500 | 1.566525 | 0.0000473340 |
17031821600 | 0.261013 | 0.0001156841 |
17031821700 | 0.045325 | 0.0001256892 |
17031821800 | 0.124497 | 0.0001452916 |
17031821900 | 0.008376 | 0.0001346883 |
17031822000 | 0.228861 | 0.0001125575 |
17031822101 | 0.095492 | 0.0001162278 |
17031822102 | 0.118435 | 0.0001133731 |
17031822200 | 0.189001 | 0.0001052983 |
17031822301 | 0.223020 | 0.0000954564 |
17031822302 | 0.074424 | 0.0001104912 |
17031822400 | 0.133506 | 0.0001604896 |
17031822500 | 0.071852 | 0.0001164997 |
17031822601 | 0.197804 | 0.0001279186 |
17031822602 | 0.116778 | 0.0001908855 |
17031822701 | 0.144444 | 0.0001224810 |
17031822702 | 0.059085 | 0.0000989364 |
17031822801 | 0.108443 | 0.0000852609 |
17031822802 | 0.101203 | 0.0000945592 |
17031822900 | 0.160214 | 0.0000501887 |
17031823001 | 0.037565 | 0.0001762041 |
17031823002 | 0.074883 | 0.0001615771 |
17031823101 | 0.081387 | 0.0001167172 |
17031823102 | 0.184112 | 0.0000960817 |
17031823200 | 0.104080 | 0.0001305558 |
17031823302 | 0.171611 | 0.0001560308 |
17031823303 | 0.129698 | 0.0001207138 |
17031823304 | 0.168865 | 0.0001642959 |
17031823400 | 0.605849 | 0.0001262058 |
17031823500 | 0.328468 | 0.0001225898 |
17031823602 | 0.106651 | 0.0001706850 |
17031823603 | 1.311968 | 0.0000619066 |
17031823604 | 0.149105 | 0.0000994258 |
17031823605 | 0.095405 | 0.0001141344 |
17031823702 | 0.007217 | 0.0001629908 |
17031823703 | 0.168774 | 0.0002340869 |
17031823704 | 0.098848 | 0.0001062771 |
17031823705 | 0.092515 | 0.0001203060 |
17031823801 | 0.112797 | 0.0001470860 |
17031823803 | 0.181463 | 0.0001768022 |
17031823805 | 0.137881 | 0.0000776212 |
17031823806 | 0.096232 | 0.0001002414 |
17031823901 | 0.196826 | 0.0001009211 |
17031823903 | 0.164596 | 0.0001221820 |
17031823904 | 0.296174 | 0.0001064402 |
17031824003 | 0.217348 | 0.0001656552 |
17031824004 | 0.128188 | 0.0001484997 |
17031824005 | 0.203341 | 0.0001536926 |
17031824006 | 0.187327 | 0.0001276739 |
17031824105 | 0.159589 | 0.0001782432 |
17031824106 | 0.116422 | 0.0001837623 |
17031824107 | 0.081088 | 0.0001837895 |
17031824108 | 0.029742 | 0.0002195143 |
17031824113 | 0.109285 | 0.0001878405 |
17031824114 | 0.113894 | 0.0001393646 |
17031824115 | 0.032983 | 0.0001099474 |
17031824116 | 0.011092 | 0.0001443672 |
17031824117 | 0.200395 | 0.0002545322 |
17031824119 | 0.157517 | 0.0001526867 |
17031824120 | 0.158614 | 0.0002397964 |
17031824121 | 0.167070 | 0.0000857231 |
17031824122 | 0.100802 | 0.0001754972 |
17031824123 | 0.140487 | 0.0001980359 |
17031824300 | 1.300675 | 0.0001277283 |
17031824400 | 0.097254 | 0.0000531793 |
17031824503 | 0.036998 | 0.0001900971 |
17031824505 | 0.056179 | 0.0001712016 |
17031824506 | 0.143617 | 0.0001856111 |
17031824507 | 0.077792 | 0.0001110078 |
17031824601 | 0.087661 | 0.0001205235 |
17031824602 | 0.045553 | 0.0001744913 |
17031824701 | 0.194612 | 0.0001070927 |
17031824702 | 0.176296 | 0.0001456994 |
17031824800 | 0.774914 | 0.0002100529 |
17031824900 | 0.812793 | 0.0000917044 |
17031825000 | 0.061099 | 0.0001256076 |
17031825200 | 0.257977 | 0.0000593238 |
17031825302 | 0.004983 | 0.0001780801 |
17031825303 | 0.083877 | 0.0001068752 |
17031825304 | 0.214770 | 0.0001175600 |
17031825400 | 0.079458 | 0.0001432525 |
17031825501 | 1.336873 | 0.0001516807 |
17031825503 | 1.187528 | 0.0001667699 |
17031825504 | 1.392290 | 0.0000943688 |
17031825505 | 1.470902 | 0.0001598099 |
17031825600 | 0.970222 | 0.0001396909 |
17031825700 | 0.827692 | 0.0001125031 |
17031825801 | 1.412910 | 0.0000915141 |
17031825802 | 1.365091 | 0.0001764216 |
17031825803 | 1.267050 | 0.0001687275 |
17031825900 | 0.946111 | 0.0000942329 |
17031826000 | 0.900549 | 0.0000794699 |
17031826100 | 0.693989 | 0.0001563842 |
17031826201 | 1.116754 | 0.0000889041 |
17031826202 | 0.805314 | 0.0001549704 |
17031826301 | 1.263478 | 0.0001044283 |
17031826303 | 1.523981 | 0.0001154938 |
17031826304 | 1.636315 | 0.0000744402 |
17031826401 | 1.644204 | 0.0001081531 |
17031826402 | 1.429938 | 0.0001305014 |
17031826500 | 1.370535 | 0.0001603808 |
17031826600 | 1.394829 | 0.0001535567 |
17031826700 | 1.383776 | 0.0001380868 |
17031826800 | 0.954023 | 0.0001361293 |
17031826901 | 1.140417 | 0.0000494002 |
17031826902 | 1.374999 | 0.0000441802 |
17031827000 | 1.500673 | 0.0001065218 |
17031827100 | 1.266802 | 0.0000652507 |
17031827200 | 1.023339 | 0.0001116059 |
17031827300 | 1.022068 | 0.0000614444 |
17031827400 | 1.202660 | 0.0001102737 |
17031827500 | 0.955846 | 0.0001389840 |
17031827600 | 1.730016 | 0.0000929823 |
17031827700 | 0.981824 | 0.0000761802 |
17031827801 | 1.139009 | 0.0001421106 |
17031827802 | 1.217675 | 0.0000977673 |
17031827804 | 1.065125 | 0.0000794156 |
17031827805 | 1.112561 | 0.0000793340 |
17031827901 | 1.299419 | 0.0000619882 |
17031827902 | 0.582365 | 0.0001150316 |
17031828000 | 0.169394 | 0.0001304470 |
17031828100 | 0.158745 | 0.0001438778 |
17031828201 | 0.424857 | 0.0001100562 |
17031828202 | 0.306380 | 0.0001211488 |
17031828300 | 0.069177 | 0.0000859406 |
17031828401 | 0.085534 | 0.0000953204 |
17031828402 | 0.264357 | 0.0001013833 |
17031828503 | 0.679252 | 0.0001128837 |
17031828504 | 0.730890 | 0.0001631268 |
17031828505 | 0.320884 | 0.0001731863 |
17031828506 | 0.758600 | 0.0002361532 |
17031828601 | 0.047294 | 0.0001072015 |
17031828602 | 0.454675 | 0.0001184572 |
17031828701 | 0.851892 | 0.0001121225 |
17031828702 | 0.757719 | 0.0001232423 |
17031828801 | 0.269255 | 0.0001450469 |
17031828802 | 0.448812 | 0.0000864572 |
17031828900 | 0.786065 | 0.0000976314 |
17031829000 | 1.726302 | 0.0000357791 |
17031829100 | 1.243248 | 0.0000959185 |
17031829200 | 0.658986 | 0.0001443672 |
17031829301 | 0.276085 | 0.0001032864 |
17031829302 | 1.042570 | 0.0001014920 |
17031829401 | 1.387950 | 0.0000297978 |
17031829402 | 0.712103 | 0.0000843909 |
17031829500 | 0.481313 | 0.0001073102 |
17031829600 | 0.132535 | 0.0000771046 |
17031829700 | 0.854576 | 0.0001097299 |
17031829800 | 0.359558 | 0.0001661446 |
17031829901 | 0.623420 | 0.0002394429 |
17031829902 | 1.006762 | 0.0001740019 |
17031830001 | 0.139643 | 0.0000617707 |
17031830003 | 1.409989 | 0.0002117386 |
17031830004 | 1.216950 | 0.0001828651 |
17031830005 | 0.930507 | 0.0001109534 |
17031830006 | 0.605363 | 0.0000807206 |
17031830007 | 1.132344 | 0.0001336008 |
17031830008 | 1.467996 | 0.0001139441 |
17031830100 | 1.090956 | 0.0000854241 |
17031830201 | 1.074421 | 0.0001440138 |
17031830202 | 0.717063 | 0.0000926288 |
17031830300 | 0.843268 | 0.0001215838 |
17031830400 | 0.542797 | 0.0001139712 |
17031830500 | 2.170664 | 0.0001060596 |
17031830600 | 0.296191 | 0.0001201701 |
17031830700 | 0.186246 | 0.0001028242 |
17031830800 | 0.158881 | 0.0000673442 |
17031830900 | 0.253453 | 0.0000790621 |
17031831000 | 0.148965 | 0.0000584810 |
17031831100 | 0.797195 | 0.0002315585 |
17031831200 | 1.486489 | 0.0001278914 |
17031831300 | 1.121197 | 0.0000265897 |
17031831400 | 0.920699 | 0.0000815906 |
17031831500 | 0.836566 | 0.0000970604 |
17031831600 | 1.048564 | 0.0002099985 |
17031831700 | 0.764272 | 0.0000659032 |
17031831800 | 0.451509 | 0.0001677215 |
17031831900 | 0.121513 | 0.0000842550 |
17031832000 | 0.168455 | 0.0000435277 |
17031832100 | 0.022122 | 0.0000958914 |
17031832200 | 0.161631 | 0.0000815634 |
17031832300 | 0.167180 | 0.0000499984 |
17031832400 | 0.126140 | 0.0000838744 |
17031832500 | 0.076304 | 0.0000891488 |
17031832600 | 0.222218 | 0.0001035039 |
17031832900 | 0.334070 | 0.0000557078 |
17031833000 | 0.054055 | 0.0001139169 |
17031833100 | 0.168131 | 0.0001976009 |
17031833300 | 0.687497 | 0.0000717486 |
17031833900 | 1.217716 | 0.0000712048 |
17031834000 | 1.728992 | 0.0000793612 |
17031834200 | 1.761887 | 0.0001317521 |
17031834300 | 1.701506 | 0.0001610061 |
17031834400 | 1.662839 | 0.0001189194 |
17031834500 | 1.802130 | 0.0000270247 |
17031834600 | 1.502294 | 0.0000457027 |
17031834700 | 1.733409 | 0.0000342022 |
17031834800 | 1.570508 | 0.0000429295 |
17031834900 | 1.739008 | 0.0000381173 |
17031835000 | 1.174267 | 0.0001518438 |
17031835100 | 1.601989 | 0.0001363740 |
17031835200 | 0.887948 | 0.0000541853 |
17031835500 | 1.544860 | 0.0000389873 |
17031835600 | 1.534201 | 0.0000241971 |
17031835700 | 1.819540 | 0.0000113917 |
17031835800 | 1.597355 | 0.0000456211 |
17031835900 | 1.365441 | 0.0000843094 |
17031836000 | 1.618009 | 0.0000756093 |
17031836100 | 1.436046 | 0.0000462736 |
17031836200 | 0.144374 | 0.0000399389 |
17031836300 | 0.369766 | 0.0000401292 |
17031836400 | 1.369585 | 0.0001017095 |
17031836500 | 1.678403 | 0.0000527171 |
17031836600 | 0.711305 | 0.0000632116 |
17031836700 | 1.135250 | 0.0000626407 |
17031836800 | 1.434525 | 0.0000651691 |
17031836900 | 1.047147 | 0.0000309397 |
17031837000 | 1.255565 | 0.0000471980 |
17031837100 | 0.920811 | 0.0000351810 |
17031837300 | 1.434365 | 0.0000746849 |
17031837400 | 1.319868 | 0.0000600578 |
17031837800 | 0.773014 | 0.0000704980 |
17031838000 | 0.782943 | 0.0000672626 |
17031838100 | 0.479755 | 0.0000436364 |
17031838200 | 0.196830 | 0.0000533968 |
17031838300 | 0.244024 | 0.0000442074 |
17031838600 | 1.465025 | 0.0000463008 |
17031838700 | 1.481704 | 0.0001069568 |
17031838800 | 1.071700 | 0.0000894750 |
17031839000 | 0.051309 | 0.0002399323 |
17031839100 | 0.247539 | 0.0001994769 |
17031839200 | 0.881831 | 0.0000606288 |
17031839500 | 0.793528 | 0.0000375735 |
17031839600 | 1.399052 | 0.0000446152 |
17031839700 | 0.679571 | 0.0001313442 |
17031839800 | 0.411158 | 0.0000738692 |
17031839900 | 0.339458 | 0.0001190282 |
17031840000 | 0.866288 | 0.0000757452 |
17031840100 | 1.539130 | 0.0000923298 |
17031840200 | 1.317108 | 0.0000641632 |
17031840300 | 1.079495 | 0.0000954564 |
17031840400 | 1.216373 | 0.0000840647 |
17031840700 | 1.407720 | 0.0000961904 |
17031840800 | 2.136251 | 0.0000856687 |
17031841000 | 0.429469 | 0.0000275141 |
17031841100 | 2.341073 | 0.0001936043 |
17031841200 | 1.135640 | 0.0001242482 |
17031841300 | 1.037437 | 0.0001108446 |
17031841400 | 1.301316 | 0.0000243875 |
17031841500 | 1.571721 | 0.0000731080 |
17031841600 | 1.308107 | 0.0000157417 |
17031841700 | 1.115776 | 0.0000448327 |
17031841800 | 1.600611 | 0.0000649788 |
17031841900 | 0.223974 | 0.0001725609 |
17031842000 | 0.348517 | 0.0000832218 |
17031842100 | 1.122936 | 0.0002119561 |
17031842200 | 0.006997 | 0.0000898285 |
17031842300 | 0.007904 | 0.0000841734 |
17031842400 | 1.675157 | 0.0000837928 |
17031842500 | 1.761703 | 0.0000557894 |
17031842600 | 0.295470 | 0.0001158472 |
17031842800 | 1.797511 | 0.0001916196 |
17031842900 | 0.940049 | 0.0000661479 |
17031843000 | 1.450751 | 0.0000659848 |
17031843100 | 1.108581 | 0.0000418692 |
17031843200 | 1.055998 | 0.0000640273 |
17031843300 | 0.978970 | 0.0000508956 |
17031843400 | 1.069479 | 0.0000356160 |
17031843500 | 0.890500 | 0.0002764727 |
17031843600 | 1.329440 | 0.0000757180 |
17031843700 | 0.165002 | 0.0000652779 |
17031843800 | 0.643482 | 0.0000411079 |
17031843900 | 1.423891 | 0.0000912694 |
17037001900 | 0.291807 | 0.0000682957 |
17037002000 | 0.232235 | 0.0001398268 |
17037002100 | 0.227503 | 0.0000586713 |
17043840000 | 0.713717 | 0.0000756093 |
17043840101 | 0.381391 | 0.0001482279 |
17043840102 | 0.095149 | 0.0001177775 |
17043840103 | 0.261444 | 0.0001684556 |
17043840104 | 0.809974 | 0.0001513001 |
17043840201 | 0.148444 | 0.0001746816 |
17043840202 | 0.189358 | 0.0001526595 |
17043840303 | 0.403618 | 0.0001027427 |
17043840304 | 0.182130 | 0.0001041836 |
17043840600 | 0.170312 | 0.0001410231 |
17043840703 | 0.375653 | 0.0001135362 |
17043840704 | 0.415803 | 0.0000853969 |
17043840705 | 0.206119 | 0.0001077180 |
17043840706 | 0.139894 | 0.0000901819 |
17043840801 | 0.503329 | 0.0000704708 |
17043840802 | 0.525912 | 0.0001535023 |
17043840901 | 0.074707 | 0.0001013561 |
17043840904 | 0.434913 | 0.0001140528 |
17043840906 | 0.184646 | 0.0000772133 |
17043840907 | 0.388193 | 0.0001195447 |
17043840908 | 0.415321 | 0.0001092406 |
17043840910 | 0.309076 | 0.0001312083 |
17043840911 | 0.626150 | 0.0000824606 |
17043841002 | 0.221510 | 0.0000826237 |
17043841003 | 0.042234 | 0.0000933085 |
17043841004 | 0.162657 | 0.0000937163 |
17043841102 | 0.069388 | 0.0001646765 |
17043841103 | 0.049519 | 0.0001000511 |
17043841104 | 0.191602 | 0.0001183757 |
17043841108 | 0.358305 | 0.0001258795 |
17043841109 | 0.128480 | 0.0001060324 |
17043841110 | 0.097586 | 0.0000901004 |
17043841111 | 0.233795 | 0.0000930638 |
17043841112 | 0.164689 | 0.0000827325 |
17043841113 | 0.235599 | 0.0000982023 |
17043841114 | 0.164276 | 0.0001167988 |
17043841204 | 0.385698 | 0.0001520613 |
17043841205 | 0.268209 | 0.0001263417 |
17043841206 | 0.129402 | 0.0001385490 |
17043841207 | 0.486909 | 0.0000798777 |
17043841208 | 0.362417 | 0.0001484726 |
17043841209 | 0.267516 | 0.0000991811 |
17043841210 | 0.321267 | 0.0001229160 |
17043841307 | 0.110555 | 0.0001590758 |
17043841308 | 0.214601 | 0.0001153306 |
17043841310 | 0.291276 | 0.0001011114 |
17043841312 | 0.693601 | 0.0001050808 |
17043841313 | 0.070015 | 0.0000774308 |
17043841314 | 0.132427 | 0.0001732406 |
17043841315 | 0.285048 | 0.0000926560 |
17043841316 | 0.182641 | 0.0000883332 |
17043841318 | 0.268264 | 0.0000752558 |
17043841320 | 0.612342 | 0.0000685948 |
17043841321 | 0.362931 | 0.0000690026 |
17043841322 | 0.471521 | 0.0001276195 |
17043841323 | 0.263554 | 0.0000759627 |
17043841324 | 0.390782 | 0.0000794427 |
17043841325 | 0.330552 | 0.0001611149 |
17043841326 | 0.147762 | 0.0000887682 |
17043841327 | 0.301692 | 0.0001175600 |
17043841401 | 0.340136 | 0.0001778898 |
17043841403 | 0.162340 | 0.0001064402 |
17043841404 | 0.217591 | 0.0000879525 |
17043841501 | 0.969616 | 0.0001697334 |
17043841503 | 1.507513 | 0.0001066305 |
17043841504 | 0.672230 | 0.0000864300 |
17043841603 | 0.412324 | 0.0001151403 |
17043841604 | 0.026584 | 0.0001121768 |
17043841605 | 0.301107 | 0.0001095124 |
17043841606 | 0.142690 | 0.0000578284 |
17043841607 | 0.098629 | 0.0001207682 |
17043841703 | 0.166091 | 0.0001836536 |
17043841704 | 0.104408 | 0.0001165269 |
17043841705 | 0.377107 | 0.0001560580 |
17043841706 | 0.686097 | 0.0001154938 |
17043841801 | 0.068012 | 0.0001356399 |
17043841802 | 0.148711 | 0.0001409415 |
17043841901 | 0.234892 | 0.0000697911 |
17043841902 | 0.068568 | 0.0001148413 |
17043842000 | 0.178852 | 0.0001085881 |
17043842100 | 0.093724 | 0.0001628277 |
17043842200 | 0.183531 | 0.0001242482 |
17043842300 | 0.209353 | 0.0000954564 |
17043842400 | 0.090517 | 0.0001343893 |
17043842500 | 0.157728 | 0.0000904266 |
17043842601 | 0.196540 | 0.0001068209 |
17043842602 | 0.245240 | 0.0001064946 |
17043842603 | 0.097502 | 0.0000998880 |
17043842604 | 0.101877 | 0.0001102737 |
17043842605 | 0.085681 | 0.0001131556 |
17043842702 | 0.098596 | 0.0001232151 |
17043842703 | 0.110291 | 0.0001049721 |
17043842704 | 0.063643 | 0.0001465694 |
17043842706 | 0.201369 | 0.0001157384 |
17043842708 | 0.173725 | 0.0000691386 |
17043842709 | 0.142680 | 0.0000989092 |
17043842710 | 0.054777 | 0.0001015736 |
17043842711 | 0.228968 | 0.0000634563 |
17043842800 | 0.168024 | 0.0001222635 |
17043842900 | 0.138312 | 0.0001541004 |
17043843000 | 0.157932 | 0.0001157928 |
17043843100 | 0.076789 | 0.0001072559 |
17043843200 | 0.233324 | 0.0001400172 |
17043843301 | 0.182953 | 0.0001168803 |
17043843302 | 0.051462 | 0.0000758268 |
17043843400 | 0.141330 | 0.0000910791 |
17043843500 | 0.107350 | 0.0001457810 |
17043843601 | 0.099296 | 0.0000922482 |
17043843602 | 0.101948 | 0.0000838744 |
17043843700 | 0.113305 | 0.0001123128 |
17043843800 | 0.102228 | 0.0000856959 |
17043843900 | 0.247532 | 0.0001142975 |
17043844001 | 0.195514 | 0.0001061412 |
17043844002 | 0.253359 | 0.0001219101 |
17043844100 | 0.163727 | 0.0001106271 |
17043844201 | 0.054578 | 0.0001365915 |
17043844202 | 0.120450 | 0.0000683229 |
17043844301 | 0.234004 | 0.0001712559 |
17043844304 | 0.597136 | 0.0001088056 |
17043844305 | 0.199693 | 0.0001044011 |
17043844306 | 0.427138 | 0.0001176416 |
17043844307 | 0.339530 | 0.0001021717 |
17043844401 | 0.164832 | 0.0000829500 |
17043844402 | 0.262238 | 0.0001231879 |
17043844501 | 0.068264 | 0.0001017367 |
17043844502 | 0.504859 | 0.0000874631 |
17043844601 | 0.112982 | 0.0001014920 |
17043844602 | 0.128858 | 0.0001286798 |
17043844701 | 0.206780 | 0.0001135091 |
17043844702 | 0.207830 | 0.0001508379 |
17043844801 | 0.232166 | 0.0001121497 |
17043844802 | 0.257895 | 0.0000856416 |
17043844901 | 0.169190 | 0.0000978761 |
17043844902 | 0.143746 | 0.0001092678 |
17043845000 | 0.069687 | 0.0001685643 |
17043845100 | 0.199921 | 0.0001713375 |
17043845200 | 0.223975 | 0.0001344980 |
17043845300 | 0.208164 | 0.0000888497 |
17043845401 | 0.269780 | 0.0001004589 |
17043845402 | 0.370156 | 0.0000809924 |
17043845502 | 0.133206 | 0.0001316433 |
17043845505 | 0.211313 | 0.0001164997 |
17043845506 | 0.215845 | 0.0000964079 |
17043845507 | 0.160975 | 0.0000902091 |
17043845508 | 0.268617 | 0.0000993170 |
17043845509 | 0.781012 | 0.0000869466 |
17043845510 | 0.316473 | 0.0000879525 |
17043845601 | 0.065433 | 0.0001091318 |
17043845602 | 0.059035 | 0.0001347427 |
17043845701 | 0.198138 | 0.0001085609 |
17043845702 | 0.151551 | 0.0001241123 |
17043845703 | 0.139499 | 0.0001268854 |
17043845704 | 0.011582 | 0.0001291692 |
17043845802 | 0.150944 | 0.0000986101 |
17043845803 | 0.197207 | 0.0001493969 |
17043845805 | 0.252593 | 0.0000982023 |
17043845807 | 0.100181 | 0.0001580155 |
17043845808 | 0.273844 | 0.0000951845 |
17043845809 | 0.191895 | 0.0001153578 |
17043845810 | 0.074424 | 0.0001040477 |
17043845811 | 0.053842 | 0.0001040205 |
17043845901 | 0.302651 | 0.0000849347 |
17043845902 | 0.351917 | 0.0000926288 |
17043846002 | 0.074905 | 0.0001214479 |
17043846003 | 0.169320 | 0.0001113612 |
17043846004 | 0.147631 | 0.0000889857 |
17043846102 | 0.102214 | 0.0001188379 |
17043846103 | 0.122214 | 0.0001479560 |
17043846104 | 0.152134 | 0.0001207138 |
17043846105 | 0.104196 | 0.0000949942 |
17043846106 | 0.259965 | 0.0001018455 |
17043846201 | 0.119534 | 0.0001560580 |
17043846202 | 0.338313 | 0.0001736485 |
17043846203 | 0.242663 | 0.0001159016 |
17043846205 | 0.250970 | 0.0001014377 |
17043846206 | 0.143383 | 0.0001148956 |
17043846207 | 0.111995 | 0.0001493154 |
17043846208 | 0.252539 | 0.0000874903 |
17043846209 | 0.213859 | 0.0001112253 |
17043846304 | 0.494758 | 0.0001690809 |
17043846305 | 0.090633 | 0.0001497776 |
17043846307 | 0.092725 | 0.0001185116 |
17043846308 | 0.154855 | 0.0000967342 |
17043846310 | 0.121562 | 0.0001251998 |
17043846311 | 0.099689 | 0.0001487988 |
17043846312 | 0.060278 | 0.0001196263 |
17043846313 | 0.193558 | 0.0001311267 |
17043846314 | 0.138833 | 0.0000900460 |
17043846315 | 0.121319 | 0.0001104096 |
17043846404 | 0.023595 | 0.0001689450 |
17043846405 | 0.274205 | 0.0000973595 |
17043846408 | 0.608213 | 0.0001078540 |
17043846409 | 0.218159 | 0.0001249279 |
17043846410 | 0.375424 | 0.0001427631 |
17043846411 | 0.365803 | 0.0001253086 |
17043846412 | 0.101378 | 0.0001207138 |
17043846413 | 0.158055 | 0.0000914597 |
17043846504 | 0.095939 | 0.0001692712 |
17043846507 | 0.396105 | 0.0000688395 |
17043846509 | 0.560090 | 0.0001502398 |
17043846510 | 0.171033 | 0.0000832490 |
17043846511 | 0.240259 | 0.0001760138 |
17043846513 | 0.446561 | 0.0000680782 |
17043846514 | 0.522833 | 0.0001084249 |
17043846515 | 0.133457 | 0.0001337368 |
17043846517 | 0.213496 | 0.0001573630 |
17043846518 | 0.138463 | 0.0000870009 |
17043846519 | 0.204343 | 0.0000766152 |
17043846521 | 0.105223 | 0.0001452372 |
17043846522 | 0.577627 | 0.0001078268 |
17043846523 | 0.286627 | 0.0000718845 |
17043846524 | 0.203972 | 0.0001277283 |
17043846603 | 1.167096 | 0.0001125847 |
17043846604 | 0.385945 | 0.0001010027 |
17043846701 | 0.646155 | 0.0001221820 |
17043846702 | 0.299487 | 0.0001054343 |
17063000102 | 0.148855 | 0.0002084488 |
17063000103 | 0.108404 | 0.0001623927 |
17073030100 | 0.213694 | 0.0001529042 |
17073030201 | 0.294060 | 0.0001242754 |
17073030203 | 0.222534 | 0.0001142975 |
17089850101 | 0.292939 | 0.0001696790 |
17089850103 | 0.218405 | 0.0001558948 |
17089850105 | 0.278419 | 0.0001903146 |
17089850106 | 0.149933 | 0.0002225321 |
17089850201 | 1.061903 | 0.0001194904 |
17089850202 | 1.135665 | 0.0001787326 |
17089850301 | 0.868744 | 0.0002263384 |
17089850302 | 0.424813 | 0.0001209857 |
17089850400 | 0.155799 | 0.0000688395 |
17089850500 | 0.072584 | 0.0001085609 |
17089850600 | 0.126567 | 0.0001976009 |
17089850701 | 0.118326 | 0.0006356235 |
17089850702 | 0.258424 | 0.0003792154 |
17089850800 | 0.857108 | 0.0001845236 |
17089851000 | 0.204072 | 0.0001748447 |
17089851101 | 0.392731 | 0.0001126934 |
17089851102 | 0.491191 | 0.0001064402 |
17089851301 | 1.080813 | 0.0001006492 |
17089851302 | 1.135556 | 0.0000918404 |
17089851400 | 1.276639 | 0.0001760410 |
17089851500 | 1.016764 | 0.0000316194 |
17089851600 | 0.943658 | 0.0001810979 |
17089851801 | 0.120078 | 0.0001969484 |
17089851904 | 0.216412 | 0.0002119017 |
17089851905 | 0.190803 | 0.0003792969 |
17089851907 | 0.184126 | 0.0002072798 |
17089851908 | 0.247843 | 0.0001447478 |
17089851909 | 0.219905 | 0.0001168260 |
17089851910 | 0.219219 | 0.0000988005 |
17089852001 | 0.096708 | 0.0001322414 |
17089852002 | 0.145323 | 0.0001896621 |
17089852003 | 0.187616 | 0.0002077963 |
17089852101 | 0.106542 | 0.0001920274 |
17089852102 | 0.153866 | 0.0002438202 |
17089852201 | 0.171070 | 0.0001192729 |
17089852202 | 0.103353 | 0.0002437114 |
17089852300 | 0.183594 | 0.0000542125 |
17089852401 | 0.186760 | 0.0002344132 |
17089852402 | 0.166607 | 0.0002283503 |
17089852403 | 0.232238 | 0.0001410231 |
17089852500 | 0.158777 | 0.0001750078 |
17089852601 | 0.189044 | 0.0002118201 |
17089852606 | 0.218574 | 0.0001280545 |
17089852700 | 0.130398 | 0.0001806085 |
17089852803 | 0.052008 | 0.0001328668 |
17089852805 | 0.144493 | 0.0001500766 |
17089852806 | 0.157529 | 0.0001854751 |
17089852807 | 0.100321 | 0.0000989364 |
17089852808 | 0.149903 | 0.0002024131 |
17089852903 | 0.221707 | 0.0001723706 |
17089852904 | 1.287648 | 0.0000777299 |
17089852905 | 0.746003 | 0.0001190825 |
17089852906 | 0.343297 | 0.0001548617 |
17089852907 | 1.175734 | 0.0001926527 |
17089853001 | 0.168955 | 0.0000812371 |
17089853004 | 0.120393 | 0.0000906169 |
17089853005 | 0.302412 | 0.0001568192 |
17089853006 | 0.280022 | 0.0000932541 |
17089853007 | 0.582508 | 0.0001542364 |
17089853008 | 0.421868 | 0.0001173425 |
17089853100 | 0.701975 | 0.0000866475 |
17089853200 | 0.713321 | 0.0001763400 |
17089853300 | 1.315903 | 0.0001381140 |
17089853400 | 1.895795 | 0.0002515415 |
17089853500 | 1.520167 | 0.0001786782 |
17089853600 | 1.114466 | 0.0002114395 |
17089853900 | 0.094913 | 0.0001605711 |
17089854001 | 0.107294 | 0.0001249823 |
17089854002 | 0.505200 | 0.0001422737 |
17089854100 | 1.598081 | 0.0001439594 |
17089854200 | 1.125739 | 0.0001584233 |
17089854301 | 1.583153 | 0.0001930062 |
17089854302 | 0.984649 | 0.0001354768 |
17089854400 | 0.546880 | 0.0003797320 |
17089854501 | 0.130529 | 0.0004130098 |
17089854503 | 0.088793 | 0.0003268245 |
17089854504 | 0.061660 | 0.0002301991 |
17089854600 | 0.675140 | 0.0001128565 |
17089854700 | 0.669458 | 0.0000601394 |
17089854800 | 0.210307 | 0.0002063282 |
17089854900 | 0.171227 | 0.0001486357 |
17093890101 | 0.078290 | 0.0005218969 |
17093890102 | 0.166718 | 0.0004001228 |
17093890201 | 0.223377 | 0.0001361021 |
17093890202 | 0.233695 | 0.0001017367 |
17093890301 | 0.096736 | 0.0001705762 |
17093890302 | 0.160794 | 0.0001736756 |
17093890400 | 0.053567 | 0.0007813229 |
17093890500 | 0.136319 | 0.0003688296 |
17093890600 | 0.146612 | 0.0002767446 |
17093890700 | 0.040031 | 0.0004404423 |
17097860101 | 0.100545 | 0.0004288603 |
17097860103 | 0.197593 | 0.0000974683 |
17097860104 | 0.108768 | 0.0001737300 |
17097860200 | 0.287930 | 0.0000969517 |
17097860301 | 0.449689 | 0.0000975770 |
17097860302 | 0.611096 | 0.0000716942 |
17097860400 | 0.268357 | 0.0001519798 |
17097860500 | 0.461802 | 0.0001143519 |
17097860600 | 0.291206 | 0.0001845780 |
17097860805 | 0.210413 | 0.0000500255 |
17097860806 | 0.183326 | 0.0001314530 |
17097860807 | 0.273200 | 0.0000908072 |
17097860808 | 0.236649 | 0.0000704164 |
17097860809 | 0.267076 | 0.0000834937 |
17097860810 | 0.072065 | 0.0001823757 |
17097860811 | 0.143567 | 0.0001102465 |
17097860903 | 0.158771 | 0.0001632355 |
17097860904 | 0.165705 | 0.0001349874 |
17097860905 | 0.212332 | 0.0001569280 |
17097860906 | 0.060314 | 0.0002567887 |
17097861007 | 0.129838 | 0.0001122856 |
17097861008 | 0.144236 | 0.0001445031 |
17097861009 | 0.122514 | 0.0001336824 |
17097861010 | 0.092047 | 0.0001597011 |
17097861011 | 0.085909 | 0.0002023860 |
17097861012 | 0.187828 | 0.0001344165 |
17097861013 | 0.017771 | 0.0000805574 |
17097861014 | 0.083551 | 0.0000990723 |
17097861105 | 0.075697 | 0.0001110350 |
17097861106 | 0.104487 | 0.0002144030 |
17097861107 | 0.094405 | 0.0001041021 |
17097861108 | 0.157874 | 0.0001562483 |
17097861201 | 0.676577 | 0.0001845508 |
17097861202 | 0.540103 | 0.0001069296 |
17097861301 | 0.381953 | 0.0001375431 |
17097861303 | 0.991083 | 0.0001273748 |
17097861304 | 1.118318 | 0.0000938523 |
17097861402 | 0.161113 | 0.0002346579 |
17097861403 | 0.902466 | 0.0000647613 |
17097861404 | 0.479356 | 0.0001640240 |
17097861504 | 0.929760 | 0.0002123911 |
17097861505 | 0.091856 | 0.0001776451 |
17097861506 | 0.152882 | 0.0001519254 |
17097861507 | 0.176776 | 0.0000795515 |
17097861508 | 0.019129 | 0.0000997248 |
17097861509 | 0.064305 | 0.0000896654 |
17097861510 | 0.132086 | 0.0001269670 |
17097861603 | 0.110386 | 0.0003054821 |
17097861604 | 0.132929 | 0.0002775874 |
17097861607 | 0.098203 | 0.0001191369 |
17097861608 | 0.058975 | 0.0000979033 |
17097861609 | 0.448523 | 0.0001208498 |
17097861610 | 0.057016 | 0.0000906441 |
17097861611 | 0.155714 | 0.0001124215 |
17097861701 | 0.319228 | 0.0000394767 |
17097861702 | 0.656388 | 0.0001155481 |
17097861803 | 0.536996 | 0.0001886561 |
17097861804 | 1.098146 | 0.0000962992 |
17097861901 | 0.511497 | 0.0000847987 |
17097861902 | 0.572906 | 0.0001702500 |
17097862000 | 1.310485 | 0.0001493154 |
17097862100 | 0.956964 | 0.0001489619 |
17097862200 | 0.391850 | 0.0001034224 |
17097862300 | 0.895630 | 0.0000704708 |
17097862401 | 0.930855 | 0.0000867563 |
17097862402 | 1.694920 | 0.0000752286 |
17097862501 | 1.572891 | 0.0001000239 |
17097862502 | 0.828725 | 0.0000707698 |
17097862603 | 1.023433 | 0.0002048057 |
17097862604 | 1.362003 | 0.0001393646 |
17097862605 | 0.472860 | 0.0001061140 |
17097862700 | 1.452651 | 0.0000994801 |
17097862800 | 1.113774 | 0.0000362957 |
17097862901 | 1.387347 | 0.0001126390 |
17097862902 | 0.969705 | 0.0000620969 |
17097863003 | 0.051712 | 0.0002348482 |
17097863004 | 0.109370 | 0.0001210129 |
17097863005 | 0.186070 | 0.0000129686 |
17097863100 | 0.921524 | 0.0000674257 |
17097863201 | 1.035395 | 0.0000942057 |
17097863202 | 0.166144 | 0.0001421378 |
17097863300 | 0.278148 | 0.0000626679 |
17097863400 | 0.111203 | 0.0001114428 |
17097863500 | 0.248722 | 0.0001194360 |
17097863601 | 0.225995 | 0.0001906952 |
17097863603 | 0.193597 | 0.0000865388 |
17097863604 | 0.159182 | 0.0000784096 |
17097863701 | 0.178816 | 0.0001320783 |
17097863702 | 0.231310 | 0.0001014649 |
17097863801 | 0.205987 | 0.0001229704 |
17097863902 | 0.389578 | 0.0001502670 |
17097863903 | 0.172796 | 0.0001085065 |
17097863904 | 0.367878 | 0.0001716637 |
17097864001 | 0.389786 | 0.0001675856 |
17097864002 | 1.014909 | 0.0001699781 |
17097864101 | 0.153204 | 0.0005948690 |
17097864105 | 0.204001 | 0.0003305492 |
17097864106 | 0.180245 | 0.0002319663 |
17097864107 | 0.165504 | 0.0001380596 |
17097864108 | 0.306026 | 0.0001491251 |
17097864203 | 0.187856 | 0.0002408839 |
17097864204 | 0.183910 | 0.0001211760 |
17097864205 | 0.157732 | 0.0005942165 |
17097864206 | 0.231048 | 0.0000989636 |
17097864303 | 0.146710 | 0.0001116875 |
17097864305 | 0.189406 | 0.0001079899 |
17097864306 | 0.223190 | 0.0000589431 |
17097864307 | 0.269938 | 0.0000422226 |
17097864308 | 0.144713 | 0.0001223179 |
17097864402 | 0.271508 | 0.0001980631 |
17097864403 | 0.214186 | 0.0001448022 |
17097864407 | 0.231265 | 0.0001479832 |
17097864408 | 0.116334 | 0.0001612780 |
17097864409 | 0.144300 | 0.0001293595 |
17097864410 | 0.256570 | 0.0001487444 |
17097864411 | 0.235186 | 0.0001400715 |
17097864412 | 0.257879 | 0.0001146238 |
17097864505 | 0.478627 | 0.0001950724 |
17097864510 | 0.690273 | 0.0001250367 |
17097864511 | 0.219234 | 0.0001686459 |
17097864512 | 0.337399 | 0.0001145694 |
17097864513 | 0.291625 | 0.0001533120 |
17097864514 | 0.501277 | 0.0000651148 |
17097864515 | 0.311871 | 0.0000730808 |
17097864516 | 0.269998 | 0.0001195719 |
17097864517 | 0.713770 | 0.0000760443 |
17097864518 | 0.418865 | 0.0001339271 |
17097864519 | 0.380073 | 0.0001244114 |
17097864520 | 0.485557 | 0.0001389840 |
17097864521 | 0.477667 | 0.0000724283 |
17097864522 | 0.250099 | 0.0001224810 |
17097864601 | 0.177681 | 0.0001029602 |
17097864602 | 0.228588 | 0.0001050265 |
17097864700 | 0.213115 | 0.0000732983 |
17097864801 | 0.124975 | 0.0001506476 |
17097864802 | 0.154346 | 0.0000765336 |
17097864901 | 0.187671 | 0.0001192457 |
17097864903 | 0.207799 | 0.0001301752 |
17097864904 | 0.238149 | 0.0000694376 |
17097865000 | 0.184418 | 0.0000330604 |
17097865200 | 0.473849 | 0.0001513817 |
17097865300 | 0.175361 | 0.0000912966 |
17097865400 | 0.110988 | 0.0001162006 |
17097865501 | 0.185029 | 0.0000585897 |
17097865502 | 0.222502 | 0.0000610910 |
17097865600 | 0.297488 | 0.0000948854 |
17097865700 | 0.187006 | 0.0001560580 |
17097865801 | 0.185520 | 0.0000840647 |
17097865802 | 0.169836 | 0.0000751471 |
17097866000 | 0.093405 | 0.0005404390 |
17097866100 | 0.870768 | 0.0000897741 |
17097866200 | 0.152061 | 0.0001592389 |
17099961701 | 0.213248 | 0.0001652746 |
17111870101 | 0.184909 | 0.0001968125 |
17111870102 | 0.233579 | 0.0001729959 |
17111870401 | 0.163245 | 0.0002194055 |
17111870500 | 0.215236 | 0.0002461039 |
17111870603 | 0.224569 | 0.0001329211 |
17111870604 | 0.161814 | 0.0001591030 |
17111870605 | 0.208473 | 0.0001671778 |
17111870606 | 0.146379 | 0.0001109262 |
17111870702 | 0.146778 | 0.0002018150 |
17111870703 | 0.251423 | 0.0001369177 |
17111870704 | 0.269643 | 0.0000960545 |
17111870803 | 0.208472 | 0.0004300022 |
17111870807 | 0.133110 | 0.0001460528 |
17111870808 | 0.086625 | 0.0000986373 |
17111870809 | 0.132423 | 0.0003470794 |
17111870810 | 0.182654 | 0.0002438202 |
17111870811 | 0.210680 | 0.0002448533 |
17111870812 | 0.182402 | 0.0001318064 |
17111870902 | 0.156611 | 0.0002195686 |
17111871104 | 0.084541 | 0.0004347872 |
17111871105 | 0.150274 | 0.0001445847 |
17111871106 | 0.148090 | 0.0002446630 |
17111871107 | 0.155621 | 0.0001423281 |
17111871108 | 0.126372 | 0.0001486085 |
17111871109 | 0.144387 | 0.0001446663 |
17111871201 | 0.193525 | 0.0001776179 |
17111871202 | 0.279650 | 0.0001533664 |
17111871205 | 0.080616 | 0.0001155209 |
17111871206 | 0.164529 | 0.0001815873 |
17111871207 | 0.147441 | 0.0001278098 |
17111871208 | 0.184313 | 0.0001041293 |
17111871209 | 0.046505 | 0.0000913510 |
17111871301 | 0.205402 | 0.0001273748 |
17111871304 | 0.145892 | 0.0000811556 |
17111871305 | 0.199135 | 0.0001714191 |
17111871306 | 0.134677 | 0.0002161974 |
17111871307 | 0.190507 | 0.0001270758 |
17111871310 | 0.191397 | 0.0001173697 |
17111871311 | 0.125274 | 0.0001128022 |
17111871402 | 0.214574 | 0.0001564114 |
17111871404 | 0.134915 | 0.0001232967 |
17111871500 | 0.148300 | 0.0003917490 |
17111871600 | 0.103212 | 0.0001401531 |
17113000102 | 0.104318 | 0.0002238915 |
17113000104 | 0.018860 | 0.0003184235 |
17113000105 | 0.155385 | 0.0001041021 |
17113000200 | 0.020009 | 0.0001182125 |
17113000301 | 0.058586 | 0.0001131828 |
17113000302 | 0.079868 | 0.0001486085 |
17113000400 | 0.155075 | 0.0000915413 |
17113000501 | 0.022885 | 0.0000646254 |
17113000502 | 0.149405 | 0.0000754461 |
17113000504 | 0.030782 | 0.0001459169 |
17113000505 | 0.206651 | 0.0001642959 |
17113001103 | 0.142713 | 0.0000775396 |
17113001104 | 0.172697 | 0.0002167955 |
17113001105 | 0.156068 | 0.0001311539 |
17113001106 | 0.101223 | 0.0000850706 |
17113001200 | 0.054045 | 0.0000669907 |
17113001301 | 0.051053 | 0.0000523365 |
17113001302 | 0.006349 | 0.0000689211 |
17113001303 | 0.036153 | 0.0000537503 |
17113001402 | 0.095995 | 0.0000879797 |
17113001403 | 0.039245 | 0.0001002414 |
17113001404 | 0.027748 | 0.0001142975 |
17113001500 | 0.130132 | 0.0000596772 |
17113001600 | 0.067120 | 0.0000724555 |
17113001700 | 0.009451 | 0.0000566050 |
17113001800 | 0.174393 | 0.0000884419 |
17113002101 | 0.045639 | 0.0001300936 |
17113002102 | 0.154187 | 0.0000435277 |
17113005101 | 0.152752 | 0.0002513512 |
17113005102 | 0.226861 | 0.0001857470 |
17113005201 | 0.265579 | 0.0000287647 |
17113005202 | 0.256424 | 0.0000862669 |
17113005400 | 0.192030 | 0.0002676910 |
17113005800 | 0.146877 | 0.0001062771 |
17113005900 | 0.041381 | 0.0001046458 |
17113006000 | 0.278435 | 0.0000994530 |
17119400101 | 0.140253 | 0.0000677792 |
17119400102 | 0.013461 | 0.0001176416 |
17119400200 | 0.040957 | 0.0001131284 |
17119400600 | 0.332642 | 0.0000623960 |
17119400700 | 1.461083 | 0.0000567953 |
17119400801 | 0.149647 | 0.0000540765 |
17119400802 | 0.090716 | 0.0001710928 |
17119400903 | 0.069672 | 0.0001367546 |
17119400904 | 0.258761 | 0.0000944776 |
17119400951 | 0.205041 | 0.0001439866 |
17119400952 | 0.033775 | 0.0000821343 |
17119401903 | 0.141826 | 0.0001194360 |
17119401904 | 0.374206 | 0.0000169108 |
17119402803 | 0.164552 | 0.0000822159 |
17119402900 | 0.091566 | 0.0001258523 |
17119403001 | 0.098524 | 0.0001310724 |
17119403002 | 0.110080 | 0.0001838711 |
17119403101 | 0.010631 | 0.0001849858 |
17119403121 | 0.096786 | 0.0002341685 |
17119403122 | 0.167959 | 0.0001561939 |
17119403200 | 0.077461 | 0.0001189738 |
17119403300 | 0.087755 | 0.0000658488 |
17119403401 | 0.056643 | 0.0001034768 |
17119403402 | 0.057740 | 0.0001697878 |
17119403502 | 0.316766 | 0.0001508379 |
17119403531 | 0.230778 | 0.0002045882 |
17119403532 | 0.220511 | 0.0001393918 |
17119403533 | 0.149913 | 0.0002742705 |
17119403534 | 0.165891 | 0.0001131828 |
17119403701 | 0.231730 | 0.0001612780 |
17119404000 | 0.108078 | 0.0000664742 |
17119404100 | 0.307227 | 0.0000825965 |
17133600101 | 0.331321 | 0.0002127717 |
17133600102 | 0.248538 | 0.0001390928 |
17143000100 | 0.638531 | 0.0000334682 |
17143000200 | 0.458860 | 0.0000483671 |
17143000300 | 0.248853 | 0.0000445064 |
17143000500 | 0.574010 | 0.0000384979 |
17143000600 | 0.562621 | 0.0000857775 |
17143000900 | 0.959110 | 0.0000722108 |
17143001200 | 0.156709 | 0.0000374376 |
17143001300 | 0.361517 | 0.0000529890 |
17143001500 | 0.160066 | 0.0000455124 |
17143001600 | 0.490255 | 0.0001014920 |
17143001800 | 0.077332 | 0.0000752830 |
17143001900 | 0.067170 | 0.0000409448 |
17143002000 | 0.039662 | 0.0000832490 |
17143002100 | 0.563777 | 0.0001252270 |
17143002200 | 0.127156 | 0.0001073918 |
17143002300 | 0.068024 | 0.0001366459 |
17143002400 | 0.083885 | 0.0001109806 |
17143002500 | 0.479980 | 0.0000930095 |
17143002600 | 0.189797 | 0.0000446967 |
17143002701 | 0.191564 | 0.0000980664 |
17143002702 | 0.047259 | 0.0000906169 |
17143002800 | 0.058241 | 0.0000895838 |
17143002900 | 0.094617 | 0.0000957554 |
17143003000 | 0.023505 | 0.0001342262 |
17143003101 | 0.008892 | 0.0001395006 |
17143003102 | 0.139906 | 0.0001585592 |
17143003200 | 0.093318 | 0.0001099746 |
17143003300 | 0.163165 | 0.0000777843 |
17143003401 | 0.192808 | 0.0002908822 |
17143003402 | 0.159101 | 0.0001015464 |
17143003601 | 0.232723 | 0.0000722380 |
17143003602 | 0.206499 | 0.0001395006 |
17143003700 | 0.309945 | 0.0000939066 |
17143003900 | 0.229365 | 0.0002001022 |
17143004101 | 0.094394 | 0.0001799016 |
17143004102 | 0.109212 | 0.0000741139 |
17143004200 | 0.162088 | 0.0000890400 |
17143004300 | 0.206765 | 0.0000606560 |
17143004400 | 0.137562 | 0.0001134819 |
17143004500 | 0.159750 | 0.0001267495 |
17143004600 | 0.275758 | 0.0001448566 |
17143004801 | 0.302041 | 0.0001256348 |
17143004802 | 0.175090 | 0.0001104640 |
17143004901 | 0.334271 | 0.0000988820 |
17143004902 | 0.278152 | 0.0001286255 |
17143005000 | 1.028151 | 0.0000552456 |
17161020100 | 0.216484 | 0.0002039900 |
17161020200 | 0.037395 | 0.0000940426 |
17161020300 | 0.058576 | 0.0001627733 |
17161020400 | 0.014872 | 0.0001601633 |
17161020600 | 0.270795 | 0.0000580731 |
17161020700 | 0.151693 | 0.0000388785 |
17161020800 | 0.206334 | 0.0001400987 |
17161020900 | 0.029729 | 0.0001443400 |
17161021000 | 0.002857 | 0.0000973323 |
17161021100 | 0.068485 | 0.0000963536 |
17161021200 | 0.226427 | 0.0001172882 |
17161021300 | 0.037604 | 0.0001307461 |
17161021400 | 0.105834 | 0.0000327613 |
17161021500 | 0.136253 | 0.0001100018 |
17161021600 | 0.169107 | 0.0000569041 |
17161021700 | 0.193646 | 0.0001018455 |
17161021800 | 0.116932 | 0.0001266951 |
17161021900 | 0.150376 | 0.0000381445 |
17161022000 | 0.104440 | 0.0001080443 |
17161022100 | 0.166417 | 0.0000678607 |
17161022200 | 0.259815 | 0.0001010299 |
17161022300 | 0.498439 | 0.0000569312 |
17161022600 | 0.300572 | 0.0000585353 |
17161022800 | 0.021310 | 0.0001459441 |
17161022900 | 0.110358 | 0.0000666373 |
17161023000 | 0.104762 | 0.0001010842 |
17161023100 | 0.181272 | 0.0000656313 |
17161023200 | 0.025645 | 0.0001390384 |
17161023300 | 0.004303 | 0.0000794971 |
17161023500 | 0.391495 | 0.0000550825 |
17161023600 | 0.773649 | 0.0000507052 |
17161023700 | 0.155734 | 0.0000562516 |
17161024000 | 0.240576 | 0.0001116331 |
17161024101 | 0.269583 | 0.0000963807 |
17161024102 | 0.109627 | 0.0001408056 |
17161024200 | 0.059276 | 0.0001083162 |
17161024300 | 0.205340 | 0.0000689754 |
17161024400 | 0.191928 | 0.0000521734 |
17161024500 | 0.165051 | 0.0000573934 |
17163500400 | 1.436514 | 0.0000451046 |
17163500500 | 1.723473 | 0.0000767511 |
17163500900 | 1.518993 | 0.0000968701 |
17163501100 | 1.769039 | 0.0000400204 |
17163501200 | 1.669719 | 0.0000702805 |
17163501300 | 1.663665 | 0.0001028242 |
17163501400 | 1.692382 | 0.0000903179 |
17163501501 | 0.520615 | 0.0000576653 |
17163501502 | 0.176441 | 0.0000728633 |
17163501602 | 0.196144 | 0.0001179678 |
17163501603 | 0.114076 | 0.0001327308 |
17163501604 | 0.123949 | 0.0001180494 |
17163501605 | 0.162702 | 0.0000673170 |
17163501700 | 0.071103 | 0.0000622057 |
17163501800 | 0.080958 | 0.0001394462 |
17163501900 | 0.095998 | 0.0000836840 |
17163502100 | 1.277459 | 0.0000584266 |
17163502200 | 1.400515 | 0.0000545659 |
17163502300 | 0.345517 | 0.0001490163 |
17163502401 | 1.756650 | 0.0000427120 |
17163502404 | 0.326160 | 0.0000883875 |
17163502500 | 1.619608 | 0.0000263178 |
17163502602 | 0.605195 | 0.0001567648 |
17163502603 | 0.810008 | 0.0000941242 |
17163502700 | 1.741014 | 0.0000239524 |
17163502800 | 1.558259 | 0.0000852337 |
17163502900 | 1.504127 | 0.0000477690 |
17163503100 | 0.214390 | 0.0001964318 |
17163503202 | 0.061744 | 0.0001584233 |
17163503211 | 0.109178 | 0.0001052983 |
17163503301 | 0.099546 | 0.0000972779 |
17163503304 | 0.106392 | 0.0001792763 |
17163503322 | 0.089941 | 0.0001937946 |
17163503323 | 0.038092 | 0.0001885746 |
17163503324 | 0.082856 | 0.0001697062 |
17163503332 | 0.106028 | 0.0001285439 |
17163503334 | 0.036353 | 0.0001551064 |
17163503402 | 0.090032 | 0.0001668515 |
17163503404 | 0.023124 | 0.0001593477 |
17163503411 | 0.120249 | 0.0000913238 |
17163503412 | 0.048693 | 0.0001529857 |
17163503413 | 0.188460 | 0.0001462975 |
17163503414 | 0.078896 | 0.0001101106 |
17163503800 | 0.062902 | 0.0000253118 |
17163503903 | 0.149017 | 0.0000988820 |
17163503904 | 0.023232 | 0.0002846019 |
17163503905 | 0.310545 | 0.0000798777 |
17163503906 | 0.283852 | 0.0001379781 |
17163504302 | 0.106630 | 0.0002046154 |
17163504303 | 0.168837 | 0.0002177743 |
17163504351 | 0.054891 | 0.0000873272 |
17163504352 | 0.064775 | 0.0001137537 |
17163504353 | 0.065174 | 0.0001123944 |
17163504354 | 0.012728 | 0.0001746000 |
17163504355 | 0.050042 | 0.0001303383 |
17163504500 | 1.732983 | 0.0001401531 |
17163504600 | 1.656573 | 0.0000506509 |
17167000100 | 0.187056 | 0.0000980936 |
17167000201 | 0.093148 | 0.0000599763 |
17167000202 | 0.082051 | 0.0000826509 |
17167000300 | 0.032198 | 0.0000732167 |
17167000400 | 0.136589 | 0.0000561156 |
17167000501 | 0.156754 | 0.0000578013 |
17167000503 | 0.114266 | 0.0000941513 |
17167000504 | 0.079838 | 0.0000683229 |
17167000600 | 0.152372 | 0.0001112797 |
17167000700 | 0.092883 | 0.0000564691 |
17167000800 | 0.539430 | 0.0000522006 |
17167000900 | 0.249068 | 0.0000651963 |
17167001001 | 0.104414 | 0.0000501071 |
17167001003 | 0.118910 | 0.0000337401 |
17167001004 | 0.077572 | 0.0001268854 |
17167001100 | 0.134330 | 0.0000622601 |
17167001200 | 0.040921 | 0.0001018183 |
17167001300 | 0.061625 | 0.0000478505 |
17167001400 | 0.202412 | 0.0000268072 |
17167001500 | 0.502110 | 0.0000264809 |
17167001600 | 0.752864 | 0.0001009755 |
17167001700 | 0.786654 | 0.0000242515 |
17167001800 | 0.168445 | 0.0000563059 |
17167001900 | 0.054540 | 0.0000864572 |
17167002000 | 0.126382 | 0.0001638880 |
17167002100 | 0.091846 | 0.0000919763 |
17167002200 | 0.056310 | 0.0000982023 |
17167002300 | 0.154933 | 0.0000507324 |
17167002400 | 0.780917 | 0.0000794427 |
17167002500 | 0.111290 | 0.0001456450 |
17167002600 | 0.132966 | 0.0000644351 |
17167002700 | 0.140670 | 0.0000848259 |
17167002801 | 0.040560 | 0.0000762618 |
17167002802 | 0.239920 | 0.0000985830 |
17167002900 | 0.098288 | 0.0001360205 |
17167003000 | 0.045924 | 0.0001612780 |
17167003100 | 0.178814 | 0.0001993409 |
17167003201 | 0.216405 | 0.0001275651 |
17167003202 | 0.250239 | 0.0001168803 |
17167003203 | 0.218359 | 0.0001636433 |
17167003300 | 0.348911 | 0.0001234870 |
17167003601 | 0.352718 | 0.0000740052 |
17167003602 | 0.234879 | 0.0001170978 |
17167003603 | 0.146993 | 0.0001483366 |
17167003604 | 0.091948 | 0.0001261514 |
17167003700 | 0.301804 | 0.0002335160 |
17167003801 | 0.265251 | 0.0000628582 |
17167003802 | 0.334958 | 0.0001632899 |
17167003901 | 0.317775 | 0.0001399900 |
17167003902 | 0.219428 | 0.0001018999 |
17179020100 | 0.189826 | 0.0000670995 |
17179020301 | 0.213444 | 0.0001108175 |
17179020302 | 0.280338 | 0.0001253357 |
17179020400 | 0.302353 | 0.0001421106 |
17179020500 | 0.254061 | 0.0001218829 |
17179020600 | 0.374206 | 0.0000527715 |
17179020700 | 0.284433 | 0.0001326764 |
17179020800 | 0.305511 | 0.0000789805 |
17179020900 | 0.259487 | 0.0000505149 |
17179021000 | 0.340538 | 0.0001475210 |
17179021101 | 0.276869 | 0.0001654377 |
17179021102 | 0.332313 | 0.0001546170 |
17179021201 | 0.235069 | 0.0001507563 |
17179021202 | 0.246652 | 0.0000879525 |
17179021203 | 0.137802 | 0.0001341174 |
17179021500 | 0.226396 | 0.0001829467 |
17179021603 | 0.277347 | 0.0001465150 |
17179021604 | 0.151446 | 0.0000555447 |
17179021605 | 0.104443 | 0.0000667732 |
17179021606 | 0.271132 | 0.0001636433 |
17179021702 | 0.282206 | 0.0001438506 |
17179021801 | 0.091900 | 0.0001397181 |
17179021802 | 0.319166 | 0.0000488565 |
17179022100 | 0.298801 | 0.0000932270 |
17179022200 | 0.226679 | 0.0001284080 |
17179022300 | 0.263565 | 0.0001609789 |
17179022400 | 0.228068 | 0.0001117690 |
17197880105 | 0.172100 | 0.0001811795 |
17197880106 | 0.305072 | 0.0001161735 |
17197880107 | 0.251125 | 0.0001420834 |
17197880109 | 0.018498 | 0.0001331930 |
17197880111 | 0.264766 | 0.0000970332 |
17197880112 | 0.155616 | 0.0000590519 |
17197880113 | 0.673670 | 0.0001085337 |
17197880114 | 0.491510 | 0.0000781649 |
17197880115 | 0.298550 | 0.0000862125 |
17197880116 | 0.211222 | 0.0000847172 |
17197880117 | 0.185345 | 0.0000857231 |
17197880118 | 0.218972 | 0.0001271029 |
17197880119 | 0.288062 | 0.0001066577 |
17197880120 | 0.254943 | 0.0002775330 |
17197880121 | 0.154491 | 0.0002610844 |
17197880202 | 0.183691 | 0.0001275651 |
17197880203 | 0.412186 | 0.0001111981 |
17197880204 | 0.194183 | 0.0001462975 |
17197880303 | 0.156377 | 0.0001068752 |
17197880304 | 0.199885 | 0.0001258795 |
17197880305 | 0.208252 | 0.0001327852 |
17197880306 | 0.535524 | 0.0001754700 |
17197880307 | 0.530455 | 0.0001613052 |
17197880308 | 0.125664 | 0.0002392798 |
17197880309 | 0.338946 | 0.0001290333 |
17197880310 | 0.136078 | 0.0003487922 |
17197880312 | 0.495380 | 0.0002992017 |
17197880313 | 0.207916 | 0.0003040411 |
17197880314 | 0.068328 | 0.0001982534 |
17197880404 | 0.044101 | 0.0003135025 |
17197880408 | 0.174680 | 0.0001469229 |
17197880410 | 0.223436 | 0.0002233477 |
17197880411 | 0.085098 | 0.0000899100 |
17197880412 | 0.068162 | 0.0001083706 |
17197880414 | 0.084309 | 0.0001141072 |
17197880415 | 0.160925 | 0.0001963231 |
17197880416 | 0.150599 | 0.0000890672 |
17197880417 | 0.060038 | 0.0000744130 |
17197880418 | 0.059903 | 0.0001387121 |
17197880419 | 0.076988 | 0.0002335160 |
17197880420 | 0.085666 | 0.0002807684 |
17197880421 | 0.042719 | 0.0001664981 |
17197880502 | 0.227255 | 0.0001434972 |
17197880503 | 0.026568 | 0.0001188379 |
17197880505 | 0.465051 | 0.0001933052 |
17197880507 | 0.364473 | 0.0001911574 |
17197880601 | 0.159897 | 0.0000807478 |
17197880602 | 0.116967 | 0.0000914869 |
17197880701 | 0.124423 | 0.0001139984 |
17197880702 | 0.352138 | 0.0000793068 |
17197880901 | 0.105809 | 0.0001548345 |
17197880903 | 0.091708 | 0.0000698998 |
17197880905 | 0.395491 | 0.0000731624 |
17197881001 | 0.176563 | 0.0001460257 |
17197881002 | 0.214655 | 0.0001423281 |
17197881005 | 0.250965 | 0.0000942601 |
17197881006 | 0.185769 | 0.0000633476 |
17197881007 | 0.128584 | 0.0001570639 |
17197881009 | 0.202607 | 0.0001785151 |
17197881010 | 0.101604 | 0.0001010842 |
17197881011 | 0.190422 | 0.0000935260 |
17197881012 | 0.211600 | 0.0000827868 |
17197881105 | 0.220781 | 0.0001871608 |
17197881107 | 0.218468 | 0.0000755549 |
17197881108 | 0.132309 | 0.0001728328 |
17197881109 | 0.152918 | 0.0001235957 |
17197881111 | 0.223846 | 0.0000743042 |
17197881112 | 0.260599 | 0.0001539917 |
17197881113 | 0.222776 | 0.0001248735 |
17197881115 | 0.259689 | 0.0001110621 |
17197881116 | 0.288904 | 0.0001073374 |
17197881200 | 0.816285 | 0.0001257979 |
17197881301 | 1.711211 | 0.0000759899 |
17197881302 | 1.818346 | 0.0000477146 |
17197881401 | 0.805684 | 0.0000985558 |
17197881402 | 0.229128 | 0.0000842278 |
17197881500 | 0.228944 | 0.0000797690 |
17197881601 | 0.067327 | 0.0000549193 |
17197881603 | 0.223601 | 0.0000912694 |
17197881604 | 0.244461 | 0.0000661207 |
17197881700 | 0.138155 | 0.0000922210 |
17197881800 | 0.313244 | 0.0001113068 |
17197881900 | 0.770571 | 0.0000966254 |
17197882000 | 0.819895 | 0.0000853425 |
17197882100 | 1.639099 | 0.0000723195 |
17197882200 | 1.023426 | 0.0001087512 |
17197882300 | 0.355288 | 0.0000999695 |
17197882400 | 1.084188 | 0.0000899372 |
17197882500 | 1.209399 | 0.0000583450 |
17197882601 | 0.254238 | 0.0000880613 |
17197882602 | 0.636136 | 0.0000763161 |
17197882701 | 0.215546 | 0.0000738692 |
17197882702 | 0.205463 | 0.0000840647 |
17197882801 | 0.173106 | 0.0000750383 |
17197882802 | 0.230130 | 0.0000852066 |
17197882900 | 0.325490 | 0.0000636194 |
17197883000 | 0.325747 | 0.0000962720 |
17197883100 | 0.445216 | 0.0001123400 |
17197883206 | 0.053240 | 0.0001041021 |
17197883208 | 0.034305 | 0.0000759355 |
17197883209 | 0.061238 | 0.0000794699 |
17197883210 | 0.026489 | 0.0000752558 |
17197883211 | 0.065632 | 0.0001604080 |
17197883212 | 0.056913 | 0.0001486357 |
17197883213 | 0.140385 | 0.0001570095 |
17197883214 | 0.025787 | 0.0000682957 |
17197883215 | 0.109350 | 0.0003234804 |
17197883216 | 0.106419 | 0.0000755005 |
17197883303 | 0.244933 | 0.0001071471 |
17197883305 | 0.229895 | 0.0000819440 |
17197883306 | 0.188849 | 0.0000954564 |
17197883307 | 0.127513 | 0.0001089687 |
17197883504 | 0.092921 | 0.0001506748 |
17197883505 | 0.019880 | 0.0002291387 |
17197883507 | 0.130572 | 0.0001081531 |
17197883509 | 0.294504 | 0.0001193544 |
17197883510 | 0.258311 | 0.0001483094 |
17197883511 | 0.093564 | 0.0001231879 |
17197883513 | 0.154706 | 0.0001541548 |
17197883514 | 0.130288 | 0.0001811795 |
17197883515 | 0.154171 | 0.0001088056 |
17197883516 | 0.232673 | 0.0002055397 |
17197883517 | 0.195853 | 0.0000931998 |
17197883519 | 0.232686 | 0.0001496144 |
17197883521 | 0.196284 | 0.0001010570 |
17197883522 | 0.225878 | 0.0000897469 |
17197883602 | 0.042670 | 0.0001499135 |
17197883603 | 0.404459 | 0.0000807206 |
17197883605 | 1.346299 | 0.0000777571 |
17197883606 | 0.742992 | 0.0001052711 |
17197883700 | 0.077199 | 0.0000838200 |
17197883803 | 0.763279 | 0.0000717486 |
17197883804 | 0.062225 | 0.0000696279 |
17197883806 | 0.147705 | 0.0000888497 |
17197883808 | 0.066997 | 0.0000495905 |
17197883809 | 0.055022 | 0.0000801768 |
17197883810 | 0.280437 | 0.0000937707 |
17197883811 | 0.027284 | 0.0000810740 |
17197884101 | 0.092831 | 0.0001222091 |
17197884103 | 0.172501 | 0.0000726730 |
17197980100 | 0.748137 | 0.0000901819 |
17201000101 | 0.187981 | 0.0001406697 |
17201000103 | 0.096096 | 0.0000728361 |
17201000104 | 0.133047 | 0.0000667460 |
17201000105 | 0.125608 | 0.0001061955 |
17201000200 | 0.200808 | 0.0000848531 |
17201000300 | 0.152635 | 0.0001053527 |
17201000401 | 0.076972 | 0.0000579916 |
17201000402 | 0.078484 | 0.0000814003 |
17201000403 | 0.057839 | 0.0001140800 |
17201000501 | 0.064839 | 0.0001321599 |
17201000502 | 0.069406 | 0.0000893663 |
17201000504 | 0.063048 | 0.0001931421 |
17201000506 | 0.015559 | 0.0001093765 |
17201000507 | 0.066659 | 0.0001021174 |
17201000510 | 0.114488 | 0.0000919763 |
17201000511 | 0.126450 | 0.0000683773 |
17201000512 | 0.056067 | 0.0001232695 |
17201000513 | 0.190253 | 0.0001074734 |
17201000514 | 0.073511 | 0.0000929823 |
17201000600 | 0.007227 | 0.0001176144 |
17201000700 | 0.094032 | 0.0000832490 |
17201000800 | 0.009956 | 0.0000622601 |
17201001000 | 0.324369 | 0.0000786271 |
17201001100 | 0.037204 | 0.0000362957 |
17201001200 | 0.298279 | 0.0000585353 |
17201001300 | 0.164265 | 0.0000566322 |
17201001400 | 0.122681 | 0.0001145966 |
17201001500 | 0.058266 | 0.0001314802 |
17201001600 | 0.155183 | 0.0001140256 |
17201001700 | 0.072488 | 0.0000760171 |
17201001800 | 0.276381 | 0.0001459441 |
17201001900 | 0.106773 | 0.0000939610 |
17201002000 | 0.122174 | 0.0000716398 |
17201002100 | 0.313905 | 0.0000443705 |
17201002200 | 0.319507 | 0.0000906169 |
17201002301 | 0.156785 | 0.0000585353 |
17201002302 | 0.104885 | 0.0000296891 |
17201002400 | 0.818088 | 0.0000602482 |
17201002500 | 0.753423 | 0.0000734614 |
17201002600 | 0.602957 | 0.0000774037 |
17201002700 | 0.962312 | 0.0000885507 |
17201002800 | 1.131285 | 0.0000354529 |
17201002900 | 0.093701 | 0.0000293628 |
17201003000 | 0.047741 | 0.0000444249 |
17201003100 | 0.259338 | 0.0000903179 |
17201003200 | 0.765307 | 0.0001002142 |
17201003300 | 0.281844 | 0.0000902907 |
17201003400 | 0.066929 | 0.0001208498 |
17201003500 | 0.108914 | 0.0000586441 |
17201003601 | 0.115895 | 0.0000445608 |
17201003602 | 0.080188 | 0.0001057877 |
17201003604 | 0.062084 | 0.0000699814 |
17201003605 | 0.045066 | 0.0000555447 |
17201003606 | 0.082955 | 0.0000693289 |
17201003705 | 0.178835 | 0.0001233510 |
17201003706 | 0.080343 | 0.0001580427 |
17201003707 | 0.012959 | 0.0000987189 |
17201003708 | 0.118373 | 0.0000773493 |
17201003709 | 0.146044 | 0.0000474155 |
17201003710 | 0.060327 | 0.0000633204 |
17201003711 | 0.083437 | 0.0001163366 |
17201003801 | 0.190922 | 0.0001604896 |
17201003805 | 0.173987 | 0.0001903418 |
17201003806 | 0.161706 | 0.0001361021 |
17201003807 | 0.023750 | 0.0002046154 |
17201003808 | 0.191797 | 0.0000861581 |
17201003809 | 0.152225 | 0.0001253357 |
17201003901 | 0.170728 | 0.0001247648 |
17201003903 | 0.254297 | 0.0001669059 |
17201003904 | 0.225936 | 0.0001228073 |
17201004001 | 0.161074 | 0.0002302263 |
17201004002 | 0.218227 | 0.0001692984 |
17201004200 | 0.249939 | 0.0001690265 |
17201980000 | 0.374206 | 0.0000001088 |
17203030501 | 0.253047 | 0.0002091013 |
17203030502 | 0.307355 | 0.0000671267 |
18003000100 | 0.052274 | 0.0000752014 |
18003000300 | 0.137086 | 0.0000889857 |
18003000400 | 0.136330 | 0.0000631029 |
18003000500 | 0.269698 | 0.0000794156 |
18003000600 | 0.111194 | 0.0000496721 |
18003000701 | 0.069664 | 0.0000840647 |
18003000704 | 0.016883 | 0.0000665014 |
18003000800 | 0.133291 | 0.0001095668 |
18003000900 | 0.153632 | 0.0000877078 |
18003001000 | 0.168444 | 0.0000323535 |
18003001100 | 0.030105 | 0.0000413526 |
18003001200 | 0.063438 | 0.0000299338 |
18003001300 | 0.061377 | 0.0000438811 |
18003001600 | 0.192195 | 0.0000545115 |
18003001700 | 0.953474 | 0.0000620154 |
18003002000 | 0.059889 | 0.0000918404 |
18003002100 | 0.225955 | 0.0000573934 |
18003002200 | 0.059060 | 0.0001139984 |
18003002300 | 0.633403 | 0.0001333018 |
18003002500 | 0.089714 | 0.0000865659 |
18003002600 | 0.192152 | 0.0001011930 |
18003002800 | 0.652597 | 0.0000612813 |
18003002900 | 0.448972 | 0.0000608463 |
18003003000 | 0.702281 | 0.0001075277 |
18003003100 | 0.192460 | 0.0000749839 |
18003003200 | 0.076259 | 0.0001298761 |
18003003301 | 0.062119 | 0.0000800952 |
18003003304 | 0.037725 | 0.0001100018 |
18003003400 | 0.105694 | 0.0001153578 |
18003003500 | 0.093133 | 0.0001108175 |
18003003600 | 0.420459 | 0.0001523060 |
18003003700 | 0.043678 | 0.0000735702 |
18003003800 | 0.066492 | 0.0000842550 |
18003003901 | 0.121072 | 0.0000933357 |
18003003902 | 0.087633 | 0.0000729992 |
18003004000 | 0.775066 | 0.0000895566 |
18003004101 | 0.056690 | 0.0000613357 |
18003004103 | 0.019057 | 0.0001593477 |
18003004300 | 0.402686 | 0.0000609279 |
18003004400 | 0.591337 | 0.0000920307 |
18003010201 | 0.248176 | 0.0001936043 |
18003010202 | 0.287655 | 0.0001622024 |
18003010304 | 0.144912 | 0.0001868889 |
18003010305 | 0.239483 | 0.0001574717 |
18003010306 | 0.207517 | 0.0001432253 |
18003010307 | 0.149936 | 0.0001523060 |
18003010308 | 0.139515 | 0.0001728328 |
18003010400 | 0.297959 | 0.0001008123 |
18003010500 | 0.219712 | 0.0000709330 |
18003010601 | 0.071146 | 0.0000925473 |
18003010602 | 0.058821 | 0.0001073102 |
18003010603 | 0.251281 | 0.0000440986 |
18003010604 | 0.153523 | 0.0000717758 |
18003010705 | 0.065253 | 0.0001386578 |
18003010706 | 0.060201 | 0.0001239492 |
18003010707 | 0.087704 | 0.0001438778 |
18003010803 | 0.140651 | 0.0001448838 |
18003010804 | 0.120222 | 0.0001146509 |
18003010807 | 0.133387 | 0.0001110893 |
18003010808 | 0.173557 | 0.0001375159 |
18003010809 | 0.016953 | 0.0001516535 |
18003010811 | 0.086463 | 0.0001471132 |
18003010812 | 0.150509 | 0.0001217470 |
18003010813 | 0.088995 | 0.0001066849 |
18003010815 | 0.125420 | 0.0001343893 |
18003010816 | 0.204838 | 0.0001250911 |
18003010817 | 0.103764 | 0.0001159288 |
18003010819 | 0.043077 | 0.0001275923 |
18003010821 | 0.034539 | 0.0001246832 |
18003010900 | 0.295825 | 0.0001805270 |
18003011000 | 0.312782 | 0.0000722652 |
18003011100 | 0.338257 | 0.0000792796 |
18003011201 | 0.135072 | 0.0000598675 |
18003011202 | 0.218291 | 0.0000777843 |
18003011204 | 0.169106 | 0.0000868378 |
18003011205 | 0.285460 | 0.0000977401 |
18003011302 | 0.858421 | 0.0001340630 |
18003011303 | 0.576784 | 0.0000497537 |
18003011304 | 0.222708 | 0.0001446935 |
18003011501 | 0.033134 | 0.0000978217 |
18003011502 | 0.111793 | 0.0000802856 |
18003011603 | 0.229920 | 0.0001761497 |
18003011604 | 0.181328 | 0.0001190282 |
18003011605 | 0.147989 | 0.0000847172 |
18003011606 | 0.088284 | 0.0001263417 |
18003011607 | 0.157250 | 0.0001385762 |
18003011608 | 0.095569 | 0.0001719900 |
18003011609 | 0.241643 | 0.0001715278 |
18003011701 | 0.270582 | 0.0000943688 |
18003011702 | 0.029987 | 0.0000911607 |
18003011801 | 0.276418 | 0.0001101106 |
18003980001 | 0.136145 | 0.0000159592 |
18003980002 | 0.374206 | 0.0000005166 |
18011810601 | 0.096246 | 0.0001859917 |
18011810603 | 0.150215 | 0.0004137983 |
18011810604 | 0.168897 | 0.0001551064 |
18011810605 | 0.200738 | 0.0001691897 |
18011810700 | 0.302799 | 0.0001349602 |
18019050100 | 0.059682 | 0.0000339304 |
18019050200 | 0.067919 | 0.0000969789 |
18019050303 | 0.124510 | 0.0000696279 |
18019050304 | 0.049186 | 0.0001427087 |
18019050305 | 0.082027 | 0.0000732167 |
18019050306 | 0.064798 | 0.0000621241 |
18019050401 | 0.196751 | 0.0000728361 |
18019050403 | 0.057587 | 0.0000745218 |
18019050404 | 0.155250 | 0.0001054343 |
18019050501 | 0.159137 | 0.0000477146 |
18019050503 | 0.097916 | 0.0001417572 |
18019050504 | 0.076600 | 0.0000853969 |
18019050603 | 0.007870 | 0.0001676671 |
18019050604 | 0.098749 | 0.0001590214 |
18019050605 | 0.048475 | 0.0001536111 |
18019050606 | 0.068635 | 0.0001190282 |
18019050701 | 0.108233 | 0.0001474122 |
18019050703 | 0.127349 | 0.0001423009 |
18019050704 | 0.186366 | 0.0001818592 |
18019050801 | 0.342776 | 0.0001868617 |
18019050803 | 0.277691 | 0.0001536111 |
18019050903 | 0.157775 | 0.0000885778 |
18019050904 | 0.228789 | 0.0001761769 |
18029080103 | 0.304475 | 0.0001554326 |
18029080104 | 0.348621 | 0.0001037758 |
18029080202 | 0.273142 | 0.0001812339 |
18029080400 | 0.280658 | 0.0001554598 |
18039000100 | 0.108598 | 0.0000762346 |
18039000200 | 0.246921 | 0.0001950996 |
18039000301 | 0.333481 | 0.0001166628 |
18039000302 | 0.158870 | 0.0001797657 |
18039000400 | 0.164557 | 0.0001376246 |
18039000501 | 0.334903 | 0.0001658184 |
18039000502 | 0.192488 | 0.0001291692 |
18039000600 | 0.152621 | 0.0002686698 |
18039000700 | 0.198252 | 0.0001881667 |
18039000802 | 0.212462 | 0.0002562178 |
18039000900 | 0.256917 | 0.0002126358 |
18039001000 | 0.213970 | 0.0001208769 |
18039001300 | 0.187372 | 0.0001861548 |
18039001400 | 0.199505 | 0.0005178731 |
18039001501 | 0.061891 | 0.0002327819 |
18039001502 | 0.228625 | 0.0003703522 |
18039001601 | 0.098849 | 0.0001210129 |
18039001602 | 0.066974 | 0.0001226170 |
18039001701 | 0.036789 | 0.0001076093 |
18039001702 | 0.161487 | 0.0001323774 |
18039001801 | 0.116100 | 0.0001096484 |
18039001802 | 0.083391 | 0.0001929518 |
18039001901 | 0.145975 | 0.0001423281 |
18039001902 | 0.140084 | 0.0001048633 |
18039002000 | 0.094470 | 0.0001985253 |
18039002101 | 0.139312 | 0.0001187835 |
18039002102 | 0.365725 | 0.0001459985 |
18039002200 | 0.180724 | 0.0002688601 |
18039002300 | 0.084285 | 0.0000618522 |
18039002400 | 0.085605 | 0.0001207954 |
18039002600 | 0.533887 | 0.0001178319 |
18039002700 | 0.175396 | 0.0000470077 |
18039002900 | 0.071022 | 0.0001292236 |
18043070200 | 0.044441 | 0.0000455124 |
18043070301 | 0.292721 | 0.0000715039 |
18043070302 | 0.153712 | 0.0000937163 |
18043070400 | 0.251041 | 0.0000729177 |
18043070500 | 0.092130 | 0.0000699542 |
18043070600 | 0.282756 | 0.0000678064 |
18043070700 | 0.069671 | 0.0000653051 |
18043070801 | 0.045163 | 0.0000899644 |
18043070802 | 0.107769 | 0.0001127206 |
18043070901 | 0.043107 | 0.0001443672 |
18043070902 | 0.060120 | 0.0000391232 |
18043071003 | 0.327077 | 0.0001914021 |
18043071004 | 0.272935 | 0.0001251182 |
18043071005 | 0.204017 | 0.0001538286 |
18043071006 | 0.032641 | 0.0001153850 |
18043071007 | 0.149336 | 0.0001334377 |
18043071101 | 0.286508 | 0.0001540189 |
18043071103 | 0.322270 | 0.0001190554 |
18043071104 | 0.278428 | 0.0001310996 |
18043071200 | 0.279587 | 0.0000483671 |
18057110100 | 0.125635 | 0.0002936554 |
18057110201 | 0.306589 | 0.0001238948 |
18057110202 | 0.249690 | 0.0001606255 |
18057110300 | 0.147424 | 0.0004534924 |
18057110401 | 0.184075 | 0.0001172066 |
18057110403 | 0.132559 | 0.0002870488 |
18057110404 | 0.197035 | 0.0001406697 |
18057110505 | 0.164270 | 0.0002041532 |
18057110506 | 0.084165 | 0.0003355246 |
18057110507 | 0.163876 | 0.0004106173 |
18057110508 | 0.152078 | 0.0003127412 |
18057110509 | 0.223643 | 0.0001383315 |
18057110511 | 0.210588 | 0.0001426816 |
18057110512 | 0.237773 | 0.0001250367 |
18057110600 | 0.178832 | 0.0001134003 |
18057110700 | 0.130592 | 0.0000752014 |
18057110804 | 0.098744 | 0.0004978629 |
18057110805 | 0.138982 | 0.0001881396 |
18057110806 | 0.084048 | 0.0003844083 |
18057110807 | 0.180412 | 0.0001748447 |
18057110808 | 0.077163 | 0.0005499547 |
18057110809 | 0.072583 | 0.0002927310 |
18057110810 | 0.105906 | 0.0001925984 |
18057110811 | 0.098587 | 0.0001230248 |
18057110812 | 0.217865 | 0.0001788685 |
18057110903 | 0.318627 | 0.0003332136 |
18057110904 | 0.228509 | 0.0001317792 |
18057110905 | 0.151180 | 0.0001077724 |
18057110906 | 0.169051 | 0.0001835448 |
18057110907 | 0.251179 | 0.0001412678 |
18057110908 | 0.163298 | 0.0003363402 |
18057111001 | 0.179989 | 0.0003434091 |
18057111003 | 0.328348 | 0.0001297945 |
18057111004 | 0.277662 | 0.0000840375 |
18057111006 | 0.110112 | 0.0001154666 |
18057111007 | 0.011430 | 0.0001128022 |
18057111008 | 0.276432 | 0.0002032560 |
18057111101 | 0.190896 | 0.0001003502 |
18057111102 | 0.171992 | 0.0002249246 |
18059410200 | 0.144723 | 0.0003392765 |
18059410300 | 0.333181 | 0.0003190216 |
18059410400 | 0.252435 | 0.0001844420 |
18059410500 | 0.286252 | 0.0000860222 |
18059410600 | 0.253966 | 0.0001454003 |
18059410700 | 0.269501 | 0.0001626102 |
18059410800 | 0.247819 | 0.0002570606 |
18059410900 | 0.090317 | 0.0002296825 |
18059411000 | 0.305121 | 0.0001683468 |
18061060500 | 0.256143 | 0.0001532032 |
18063210102 | 0.096379 | 0.0005296998 |
18063210103 | 0.287652 | 0.0001050265 |
18063210104 | 0.087364 | 0.0002308788 |
18063210201 | 0.076697 | 0.0000973051 |
18063210202 | 0.180540 | 0.0002390079 |
18063210300 | 0.233298 | 0.0001850130 |
18063210501 | 0.277913 | 0.0001858830 |
18063210502 | 0.078383 | 0.0001705219 |
18063210603 | 0.085922 | 0.0002654888 |
18063210604 | 0.031174 | 0.0004265765 |
18063210605 | 0.174193 | 0.0002822365 |
18063210606 | 0.019412 | 0.0003589333 |
18063210607 | 0.011895 | 0.0001531760 |
18063210608 | 0.194101 | 0.0000925744 |
18063210700 | 0.116386 | 0.0003282111 |
18063210801 | 0.112593 | 0.0000905082 |
18063210802 | 0.084051 | 0.0001257164 |
18063210900 | 0.283925 | 0.0000870281 |
18063211000 | 0.205826 | 0.0001604080 |
18081610100 | 0.122389 | 0.0004999564 |
18081610201 | 0.071030 | 0.0001271573 |
18081610202 | 0.041356 | 0.0002544778 |
18081610300 | 0.109667 | 0.0000957282 |
18081610401 | 0.150702 | 0.0001454275 |
18081610403 | 0.097419 | 0.0001589942 |
18081610404 | 0.167098 | 0.0001280817 |
18081610500 | 0.301497 | 0.0002398507 |
18081610603 | 0.301490 | 0.0001935771 |
18081610604 | 0.271700 | 0.0002399595 |
18081610605 | 0.182110 | 0.0001361565 |
18081610606 | 0.177041 | 0.0001424641 |
18081610701 | 0.240996 | 0.0003506682 |
18081610702 | 0.344803 | 0.0001951268 |
18081610801 | 0.284809 | 0.0002007275 |
18081610802 | 0.201312 | 0.0002130164 |
18081610900 | 0.328181 | 0.0001305558 |
18081611000 | 0.192585 | 0.0001145694 |
18081611100 | 0.321027 | 0.0000910519 |
18081611200 | 0.240291 | 0.0001285167 |
18089010100 | 0.446820 | 0.0001236501 |
18089010201 | 0.752325 | 0.0001600546 |
18089010203 | 1.637076 | 0.0000620697 |
18089010205 | 1.240963 | 0.0000376007 |
18089010302 | 1.539902 | 0.0000909976 |
18089010304 | 1.201086 | 0.0000785455 |
18089010400 | 1.551431 | 0.0000886866 |
18089010500 | 1.596799 | 0.0000200374 |
18089010600 | 1.364489 | 0.0000264809 |
18089010900 | 1.487808 | 0.0000279219 |
18089011000 | 1.244876 | 0.0000455124 |
18089011100 | 1.690842 | 0.0001358574 |
18089011200 | 1.589960 | 0.0001257164 |
18089011300 | 1.497261 | 0.0000495634 |
18089011400 | 0.958651 | 0.0000386339 |
18089011500 | 0.949436 | 0.0000701717 |
18089011600 | 1.468797 | 0.0000564962 |
18089011700 | 1.534376 | 0.0000162583 |
18089011800 | 1.552506 | 0.0000339847 |
18089011900 | 1.613001 | 0.0000390417 |
18089012000 | 1.464293 | 0.0000251487 |
18089012100 | 1.264351 | 0.0000135939 |
18089012200 | 1.819540 | 0.0000337129 |
18089012300 | 1.017849 | 0.0000559253 |
18089012400 | 1.210854 | 0.0001126662 |
18089012500 | 1.092244 | 0.0001241395 |
18089012600 | 1.279320 | 0.0000571487 |
18089012700 | 1.195077 | 0.0000885507 |
18089012800 | 1.302771 | 0.0000729449 |
18089020100 | 0.306826 | 0.0001252814 |
18089020200 | 0.420016 | 0.0000771862 |
18089020300 | 0.665684 | 0.0001613052 |
18089020400 | 0.977676 | 0.0001483910 |
18089020500 | 1.032980 | 0.0000951301 |
18089020600 | 0.733828 | 0.0000520103 |
18089020700 | 0.665826 | 0.0001287614 |
18089020800 | 1.044904 | 0.0000896110 |
18089020900 | 0.107045 | 0.0001045915 |
18089021000 | 0.404187 | 0.0001552423 |
18089021100 | 0.332763 | 0.0000717758 |
18089021300 | 0.148969 | 0.0000920035 |
18089021400 | 0.419380 | 0.0001188379 |
18089021500 | 0.211404 | 0.0000719661 |
18089021600 | 0.308369 | 0.0000761802 |
18089021700 | 0.254844 | 0.0001230792 |
18089021800 | 0.288729 | 0.0000916229 |
18089021900 | 0.304440 | 0.0001360749 |
18089022000 | 0.136459 | 0.0001200069 |
18089030100 | 1.604459 | 0.0000365404 |
18089030200 | 1.317093 | 0.0000365948 |
18089030300 | 1.035639 | 0.0000452405 |
18089030400 | 1.380364 | 0.0000877894 |
18089030500 | 1.253442 | 0.0001160103 |
18089030600 | 1.108830 | 0.0001166085 |
18089030700 | 0.909698 | 0.0000516568 |
18089030800 | 1.448161 | 0.0001299577 |
18089030900 | 1.036023 | 0.0001011386 |
18089031000 | 1.219623 | 0.0000408633 |
18089040100 | 0.296751 | 0.0000433102 |
18089040200 | 0.477290 | 0.0000847987 |
18089040300 | 0.058110 | 0.0002049144 |
18089040401 | 0.170150 | 0.0001343077 |
18089040402 | 0.070126 | 0.0001093221 |
18089040403 | 0.137328 | 0.0001559492 |
18089040501 | 0.048315 | 0.0000935260 |
18089040502 | 0.065731 | 0.0000860494 |
18089040600 | 0.089835 | 0.0000931726 |
18089040700 | 0.152298 | 0.0001213663 |
18089040801 | 0.166028 | 0.0001026883 |
18089040802 | 0.143418 | 0.0001047274 |
18089040900 | 0.100052 | 0.0001813154 |
18089041001 | 0.305430 | 0.0001166900 |
18089041002 | 0.111455 | 0.0001313171 |
18089041100 | 0.241135 | 0.0000514393 |
18089041200 | 0.233276 | 0.0000639457 |
18089041302 | 0.123787 | 0.0000673170 |
18089041400 | 0.081155 | 0.0000722924 |
18089041500 | 0.501258 | 0.0000427664 |
18089041600 | 0.256537 | 0.0001078268 |
18089041700 | 0.165289 | 0.0001200069 |
18089041800 | 0.164855 | 0.0001604896 |
18089041900 | 0.084308 | 0.0001216382 |
18089042000 | 0.096989 | 0.0001710928 |
18089042100 | 0.107410 | 0.0001465966 |
18089042200 | 0.124273 | 0.0001731863 |
18089042300 | 0.001026 | 0.0001698965 |
18089042401 | 0.540571 | 0.0001606799 |
18089042402 | 0.261056 | 0.0001674768 |
18089042403 | 0.633178 | 0.0001011386 |
18089042501 | 0.253397 | 0.0001696247 |
18089042503 | 0.252578 | 0.0000802856 |
18089042504 | 0.027731 | 0.0002082857 |
18089042505 | 0.216749 | 0.0001910215 |
18089042602 | 0.069545 | 0.0001643774 |
18089042605 | 0.095868 | 0.0002376485 |
18089042606 | 0.024121 | 0.0000798234 |
18089042607 | 0.134336 | 0.0001718541 |
18089042608 | 0.179145 | 0.0001253629 |
18089042609 | 0.133984 | 0.0002349841 |
18089042702 | 0.076823 | 0.0001403434 |
18089042703 | 0.098381 | 0.0001360205 |
18089042704 | 0.075530 | 0.0001089143 |
18089042801 | 0.087539 | 0.0002434395 |
18089042802 | 0.083087 | 0.0001414037 |
18089042901 | 0.240392 | 0.0001839798 |
18089042902 | 0.151781 | 0.0001791676 |
18089043001 | 0.172454 | 0.0001150044 |
18089043002 | 0.191021 | 0.0001398540 |
18089043101 | 0.279295 | 0.0000786543 |
18089043102 | 0.186243 | 0.0002311235 |
18089043201 | 0.263188 | 0.0000966798 |
18089043202 | 0.089695 | 0.0002358269 |
18089043300 | 0.128978 | 0.0002997726 |
18089043401 | 0.272436 | 0.0001846867 |
18089043405 | 0.257518 | 0.0001458625 |
18095011800 | 0.204945 | 0.0001985525 |
18097310103 | 0.056193 | 0.0002080682 |
18097310104 | 0.061875 | 0.0000790349 |
18097310105 | 0.159750 | 0.0001006492 |
18097310106 | 0.228676 | 0.0001086424 |
18097310108 | 0.040010 | 0.0000864300 |
18097310110 | 0.225222 | 0.0000811556 |
18097310111 | 0.411380 | 0.0001010570 |
18097310201 | 0.305115 | 0.0001032864 |
18097310203 | 0.363891 | 0.0001481735 |
18097310204 | 0.730778 | 0.0001510826 |
18097310305 | 0.595186 | 0.0001514360 |
18097310306 | 0.924723 | 0.0001570911 |
18097310308 | 0.604951 | 0.0000863756 |
18097310309 | 0.899192 | 0.0001030689 |
18097310310 | 0.510779 | 0.0001347427 |
18097310311 | 0.598242 | 0.0001714734 |
18097310312 | 0.648304 | 0.0001856111 |
18097320105 | 0.025586 | 0.0001148956 |
18097320106 | 0.062214 | 0.0000650332 |
18097320107 | 0.076544 | 0.0000542940 |
18097320108 | 0.269291 | 0.0001499951 |
18097320109 | 0.107665 | 0.0000652507 |
18097320202 | 0.171657 | 0.0001213391 |
18097320203 | 0.057545 | 0.0000741139 |
18097320204 | 0.098964 | 0.0001524692 |
18097320301 | 0.180633 | 0.0000882244 |
18097320303 | 0.053413 | 0.0000920307 |
18097320304 | 0.075199 | 0.0001829739 |
18097320400 | 0.029909 | 0.0000737061 |
18097320500 | 0.053195 | 0.0000901004 |
18097320600 | 0.197920 | 0.0000623144 |
18097320700 | 0.249749 | 0.0000537231 |
18097320800 | 0.158023 | 0.0000798777 |
18097320901 | 0.022765 | 0.0001726697 |
18097320902 | 0.440852 | 0.0001123128 |
18097320903 | 0.742517 | 0.0001337640 |
18097321001 | 0.270916 | 0.0000759899 |
18097321002 | 0.307244 | 0.0001178047 |
18097321100 | 0.170252 | 0.0000921394 |
18097321200 | 0.184243 | 0.0001329211 |
18097321300 | 0.198334 | 0.0000710961 |
18097321400 | 0.031228 | 0.0001434700 |
18097321600 | 0.201351 | 0.0001532304 |
18097321700 | 0.094212 | 0.0001081259 |
18097321800 | 0.152622 | 0.0000909704 |
18097321900 | 0.083653 | 0.0001489076 |
18097322000 | 0.348464 | 0.0000911607 |
18097322100 | 0.264898 | 0.0000719389 |
18097322200 | 0.059010 | 0.0000587256 |
18097322300 | 0.079775 | 0.0000654954 |
18097322400 | 0.077978 | 0.0000756908 |
18097322500 | 0.481952 | 0.0000408361 |
18097322600 | 1.256951 | 0.0001017095 |
18097322700 | 0.807721 | 0.0000511946 |
18097330103 | 0.050289 | 0.0001239764 |
18097330105 | 0.005570 | 0.0001339815 |
18097330106 | 0.005082 | 0.0001083977 |
18097330107 | 0.056981 | 0.0001659815 |
18097330108 | 0.163352 | 0.0001005405 |
18097330109 | 0.139507 | 0.0001299033 |
18097330202 | 0.560374 | 0.0003059715 |
18097330203 | 0.108525 | 0.0001574445 |
18097330204 | 0.109325 | 0.0001645677 |
18097330206 | 0.050580 | 0.0001294955 |
18097330208 | 0.048613 | 0.0000768871 |
18097330209 | 0.117477 | 0.0002486596 |
18097330401 | 0.182478 | 0.0001726697 |
18097330500 | 0.714909 | 0.0001708209 |
18097330600 | 0.109018 | 0.0001676128 |
18097330700 | 0.332494 | 0.0001526323 |
18097330803 | 0.580057 | 0.0001007308 |
18097330804 | 0.647169 | 0.0000826781 |
18097330805 | 0.377004 | 0.0000652507 |
18097330806 | 0.576969 | 0.0001086968 |
18097330900 | 1.017453 | 0.0001642143 |
18097331000 | 1.236298 | 0.0000999967 |
18097340101 | 0.018298 | 0.0001063587 |
18097340102 | 0.132651 | 0.0000965711 |
18097340108 | 0.602559 | 0.0000639729 |
18097340109 | 0.331166 | 0.0000301241 |
18097340110 | 0.594129 | 0.0001264504 |
18097340111 | 0.064751 | 0.0000990723 |
18097340112 | 0.222322 | 0.0001319968 |
18097340113 | 0.035620 | 0.0001099746 |
18097340114 | 0.020927 | 0.0001023349 |
18097340201 | 0.363413 | 0.0000920579 |
18097340202 | 0.245623 | 0.0001101106 |
18097340300 | 0.950584 | 0.0002382467 |
18097340400 | 0.540573 | 0.0000930638 |
18097340500 | 0.740173 | 0.0001515448 |
18097340600 | 0.711894 | 0.0001448022 |
18097340700 | 0.487007 | 0.0001154122 |
18097340800 | 0.209732 | 0.0000455667 |
18097340901 | 0.029847 | 0.0000982839 |
18097340902 | 0.172812 | 0.0001583145 |
18097341000 | 0.172466 | 0.0000432286 |
18097341100 | 0.168749 | 0.0000620154 |
18097341200 | 1.095362 | 0.0000653595 |
18097341600 | 0.786382 | 0.0000496177 |
18097341700 | 0.163144 | 0.0001235142 |
18097341902 | 0.018956 | 0.0000957282 |
18097341903 | 0.686751 | 0.0001591574 |
18097341904 | 0.480097 | 0.0000629941 |
18097342000 | 0.112314 | 0.0001737300 |
18097342101 | 0.116058 | 0.0001492066 |
18097342200 | 0.092059 | 0.0001536111 |
18097342300 | 0.175190 | 0.0001744369 |
18097342400 | 0.199936 | 0.0000423042 |
18097342500 | 0.216913 | 0.0001200069 |
18097342600 | 0.383283 | 0.0000926288 |
18097350100 | 0.877161 | 0.0000325982 |
18097350300 | 0.645614 | 0.0000696279 |
18097350400 | 0.513240 | 0.0000694104 |
18097350500 | 1.083363 | 0.0000586441 |
18097350600 | 1.249091 | 0.0001433884 |
18097350700 | 1.199594 | 0.0000414342 |
18097350800 | 1.530125 | 0.0000454580 |
18097350900 | 0.722798 | 0.0000407273 |
18097351000 | 0.753670 | 0.0000665557 |
18097351200 | 1.418640 | 0.0000688123 |
18097351500 | 0.570957 | 0.0000459202 |
18097351600 | 0.081080 | 0.0000629941 |
18097351700 | 0.409580 | 0.0000616075 |
18097351900 | 1.389933 | 0.0000714495 |
18097352100 | 0.891833 | 0.0000506781 |
18097352300 | 0.990388 | 0.0000288463 |
18097352400 | 0.268052 | 0.0000715583 |
18097352500 | 0.104987 | 0.0000755821 |
18097352600 | 0.242564 | 0.0000967070 |
18097352700 | 0.222826 | 0.0000641088 |
18097352800 | 1.263704 | 0.0000288191 |
18097353300 | 0.046846 | 0.0000632388 |
18097353500 | 0.197921 | 0.0000616075 |
18097353600 | 0.519003 | 0.0000811556 |
18097354200 | 0.050372 | 0.0002074429 |
18097354400 | 0.095763 | 0.0000404826 |
18097354500 | 0.034698 | 0.0000546203 |
18097354700 | 0.250875 | 0.0000404011 |
18097354800 | 0.271509 | 0.0000430655 |
18097354900 | 0.239119 | 0.0000724827 |
18097355000 | 0.060910 | 0.0000578013 |
18097355100 | 0.378085 | 0.0000492371 |
18097355300 | 0.043333 | 0.0000606560 |
18097355400 | 0.080689 | 0.0000805303 |
18097355500 | 0.055364 | 0.0001059780 |
18097355600 | 0.094125 | 0.0000553000 |
18097355700 | 0.090748 | 0.0000558709 |
18097355900 | 0.107281 | 0.0000531250 |
18097356200 | 0.086037 | 0.0001060596 |
18097356400 | 0.146933 | 0.0000961360 |
18097356900 | 0.061213 | 0.0000578013 |
18097357000 | 0.139298 | 0.0000585897 |
18097357100 | 0.083135 | 0.0000564691 |
18097357200 | 0.042527 | 0.0000623144 |
18097357300 | 0.097346 | 0.0000563875 |
18097357400 | 0.122928 | 0.0001360205 |
18097357500 | 0.147725 | 0.0001083434 |
18097357600 | 0.035968 | 0.0001720716 |
18097357800 | 0.147774 | 0.0000484487 |
18097357900 | 0.056668 | 0.0000912151 |
18097358000 | 0.021858 | 0.0000323535 |
18097358100 | 0.042494 | 0.0000758811 |
18097360101 | 0.586410 | 0.0000622057 |
18097360102 | 1.139613 | 0.0000570944 |
18097360201 | 0.473650 | 0.0000901547 |
18097360202 | 0.404238 | 0.0000848531 |
18097360301 | 0.126211 | 0.0000946951 |
18097360302 | 0.572195 | 0.0000621241 |
18097360401 | 0.743894 | 0.0001667699 |
18097360402 | 0.473869 | 0.0000482312 |
18097360404 | 0.706683 | 0.0001996128 |
18097360405 | 0.623786 | 0.0001660359 |
18097360501 | 0.217156 | 0.0001563570 |
18097360502 | 0.143953 | 0.0001679934 |
18097360601 | 0.015549 | 0.0001293323 |
18097360602 | 0.103205 | 0.0001639696 |
18097360700 | 0.125475 | 0.0000523365 |
18097360800 | 0.120943 | 0.0000592422 |
18097360900 | 0.203500 | 0.0001509466 |
18097361000 | 0.220436 | 0.0000648701 |
18097361100 | 0.121767 | 0.0000924385 |
18097361200 | 0.061605 | 0.0000878710 |
18097361300 | 0.161045 | 0.0000548922 |
18097361400 | 0.020083 | 0.0002848465 |
18097361600 | 0.049531 | 0.0002549943 |
18097370201 | 0.160137 | 0.0001199797 |
18097370202 | 0.059431 | 0.0001642143 |
18097370301 | 0.062285 | 0.0002795993 |
18097370302 | 0.055313 | 0.0002440920 |
18097380100 | 0.055195 | 0.0005649080 |
18097380200 | 0.117984 | 0.0000872185 |
18097380300 | 0.072817 | 0.0001223179 |
18097380402 | 0.142224 | 0.0001285439 |
18097380403 | 0.146982 | 0.0001175600 |
18097380404 | 0.081883 | 0.0001009483 |
18097380501 | 0.209279 | 0.0000584538 |
18097380502 | 0.027730 | 0.0000985558 |
18097380600 | 0.035911 | 0.0001407784 |
18097380700 | 0.312388 | 0.0001594292 |
18097380800 | 0.181915 | 0.0000734614 |
18097380901 | 0.302431 | 0.0001313986 |
18097380902 | 0.124323 | 0.0001574173 |
18097381001 | 0.533001 | 0.0001746816 |
18097381002 | 0.252248 | 0.0000823790 |
18097381101 | 0.126575 | 0.0001476025 |
18097381102 | 0.457635 | 0.0001733494 |
18097381201 | 0.288674 | 0.0001838439 |
18097381203 | 0.443650 | 0.0000814818 |
18097381204 | 0.198858 | 0.0000765065 |
18097381205 | 0.214839 | 0.0001756604 |
18097390101 | 0.063080 | 0.0002427326 |
18097390102 | 0.060950 | 0.0001550520 |
18097390200 | 0.050829 | 0.0001224810 |
18097390300 | 0.277526 | 0.0001535839 |
18097390402 | 0.110146 | 0.0003194294 |
18097390403 | 0.176392 | 0.0002768805 |
18097390404 | 0.110484 | 0.0001463519 |
18097390405 | 0.086364 | 0.0001131828 |
18097390500 | 0.786973 | 0.0000578013 |
18097390600 | 0.245909 | 0.0001393103 |
18097390700 | 0.313335 | 0.0000827868 |
18097390800 | 0.027032 | 0.0001013561 |
18097390900 | 0.149041 | 0.0000745761 |
18097391000 | 0.181523 | 0.0001681837 |
18105000100 | 0.150824 | 0.0001190282 |
18105000201 | 0.266080 | 0.0001823486 |
18105000202 | 0.145165 | 0.0001717997 |
18105000301 | 0.141856 | 0.0001158744 |
18105000302 | 0.196337 | 0.0000853969 |
18105000401 | 0.069824 | 0.0001122856 |
18105000402 | 0.076590 | 0.0001406968 |
18105000501 | 0.101652 | 0.0001333018 |
18105000502 | 0.083987 | 0.0000824062 |
18105000601 | 0.079080 | 0.0000979033 |
18105000602 | 0.078946 | 0.0000924113 |
18105000700 | 0.214920 | 0.0000818353 |
18105000800 | 0.170863 | 0.0001554598 |
18105000901 | 0.208724 | 0.0000829500 |
18105000903 | 0.130978 | 0.0001355312 |
18105000904 | 0.604625 | 0.0001439594 |
18105001001 | 0.195888 | 0.0001472763 |
18105001002 | 0.166588 | 0.0001623383 |
18105001101 | 0.051402 | 0.0001569280 |
18105001102 | 0.119798 | 0.0001298217 |
18105001103 | 0.263190 | 0.0000697095 |
18105001200 | 0.245284 | 0.0001644590 |
18105001301 | 0.255277 | 0.0001537470 |
18105001303 | 0.328192 | 0.0001621752 |
18105001304 | 0.322152 | 0.0001110078 |
18105001305 | 0.326716 | 0.0000664198 |
18105001402 | 0.277505 | 0.0001473035 |
18105001501 | 0.255621 | 0.0001538557 |
18105001600 | 0.145355 | 0.0001498319 |
18109510100 | 0.288670 | 0.0002663317 |
18109510201 | 0.278378 | 0.0001188107 |
18109510202 | 0.294845 | 0.0001022533 |
18109510300 | 0.322647 | 0.0001350418 |
18109510402 | 0.287815 | 0.0001523332 |
18109510500 | 0.264222 | 0.0001162822 |
18109510600 | 0.326614 | 0.0002279697 |
18127050101 | 0.128292 | 0.0002556740 |
18127050103 | 0.190708 | 0.0002143758 |
18127050202 | 0.112856 | 0.0001783248 |
18127050203 | 0.203845 | 0.0001739203 |
18127050300 | 0.167545 | 0.0001930605 |
18127050402 | 0.111029 | 0.0002141855 |
18127050405 | 0.281043 | 0.0000308310 |
18127050407 | 0.082736 | 0.0000927376 |
18127050501 | 0.087927 | 0.0001590214 |
18127050503 | 0.067168 | 0.0001362109 |
18127050505 | 0.136881 | 0.0000693017 |
18127050506 | 0.112539 | 0.0001589399 |
18127050507 | 0.027459 | 0.0001030146 |
18127050508 | 0.070791 | 0.0001671506 |
18127050509 | 0.078400 | 0.0001212576 |
18127050602 | 0.148678 | 0.0001278914 |
18127050603 | 0.226304 | 0.0001032593 |
18127050604 | 0.183047 | 0.0002256587 |
18127050702 | 0.096908 | 0.0002265559 |
18127050703 | 0.268113 | 0.0000844181 |
18127050704 | 0.213269 | 0.0001448566 |
18127050800 | 0.054657 | 0.0001716909 |
18127050900 | 0.088108 | 0.0001210401 |
18127051002 | 0.183689 | 0.0002342501 |
18127051005 | 0.178242 | 0.0001295770 |
18127051006 | 0.213217 | 0.0001109534 |
18127051007 | 0.201918 | 0.0001974650 |
18127051008 | 0.268458 | 0.0000580731 |
18129040400 | 0.323263 | 0.0001545354 |
18141000100 | 0.296495 | 0.0000567681 |
18141000200 | 0.441636 | 0.0001048361 |
18141000301 | 0.051099 | 0.0000615804 |
18141000302 | 0.304339 | 0.0000654138 |
18141000400 | 0.259036 | 0.0000527443 |
18141000500 | 0.939709 | 0.0000440442 |
18141000600 | 0.411880 | 0.0000566866 |
18141000700 | 0.071492 | 0.0000455396 |
18141000800 | 0.142214 | 0.0000451589 |
18141000900 | 0.002520 | 0.0000301785 |
18141001000 | 0.229103 | 0.0000833034 |
18141001100 | 0.024938 | 0.0001096212 |
18141001200 | 0.115770 | 0.0000621785 |
18141001300 | 0.013311 | 0.0000489924 |
18141001400 | 0.048097 | 0.0000806118 |
18141001500 | 0.014735 | 0.0000824334 |
18141001600 | 0.102680 | 0.0000563875 |
18141001700 | 0.070963 | 0.0000313203 |
18141001900 | 0.375924 | 0.0000225387 |
18141002000 | 0.532104 | 0.0000409720 |
18141002100 | 1.045749 | 0.0000410264 |
18141002200 | 0.964542 | 0.0000809924 |
18141002300 | 1.113967 | 0.0000307766 |
18141002400 | 0.689145 | 0.0000774308 |
18141002500 | 0.443474 | 0.0000605472 |
18141002600 | 0.459045 | 0.0000932813 |
18141002700 | 0.384047 | 0.0000514665 |
18141002800 | 0.631488 | 0.0000638913 |
18141002900 | 0.635599 | 0.0000298522 |
18141003000 | 0.167116 | 0.0000412983 |
18141003100 | 0.019610 | 0.0001038030 |
18141003200 | 0.058857 | 0.0001408056 |
18141003300 | 0.108934 | 0.0000887682 |
18141003400 | 0.294117 | 0.0000989908 |
18141003500 | 0.076263 | 0.0000721292 |
18141010100 | 0.213580 | 0.0000726730 |
18141010200 | 0.107770 | 0.0001476841 |
18141010300 | 0.160920 | 0.0001542636 |
18141010400 | 0.147982 | 0.0000899644 |
18141010500 | 0.134567 | 0.0000790621 |
18141010600 | 0.166047 | 0.0000893119 |
18141010700 | 0.054942 | 0.0000903450 |
18141010900 | 0.116816 | 0.0002066544 |
18141011000 | 0.057627 | 0.0001883027 |
18141011100 | 0.055811 | 0.0001157384 |
18141011201 | 0.132115 | 0.0000163942 |
18141011202 | 0.095940 | 0.0002188346 |
18141011301 | 0.034009 | 0.0001490435 |
18141011302 | 0.086957 | 0.0001663349 |
18141011303 | 0.086197 | 0.0001616315 |
18141011304 | 0.102564 | 0.0000605200 |
18141011305 | 0.164516 | 0.0001181854 |
18141011306 | 0.129291 | 0.0000819440 |
18141011403 | 0.111098 | 0.0001579339 |
18141011404 | 0.259190 | 0.0001802823 |
18141011405 | 0.221868 | 0.0000965167 |
18141011406 | 0.169150 | 0.0001366731 |
18141011501 | 0.007042 | 0.0001036399 |
18141011503 | 0.167264 | 0.0000506781 |
18141011504 | 0.274744 | 0.0000400748 |
18141011505 | 0.127450 | 0.0000810740 |
18141011506 | 0.030327 | 0.0001340902 |
18141011601 | 0.279586 | 0.0004340804 |
18141011602 | 0.171296 | 0.0004180396 |
18141011701 | 0.094591 | 0.0001058693 |
18141011702 | 0.086982 | 0.0002143486 |
18141011801 | 0.223800 | 0.0000350179 |
18141011802 | 0.120272 | 0.0001695159 |
18141011900 | 0.178660 | 0.0001033136 |
18141012000 | 0.268488 | 0.0001121497 |
18145710200 | 0.329747 | 0.0001437419 |
18157000100 | 0.102134 | 0.0000784640 |
18157000200 | 0.077782 | 0.0000509227 |
18157000300 | 0.108893 | 0.0000942329 |
18157000400 | 0.010613 | 0.0001128565 |
18157000700 | 0.065076 | 0.0001017095 |
18157000800 | 0.097354 | 0.0000522821 |
18157001000 | 0.235003 | 0.0000372201 |
18157001100 | 0.134251 | 0.0000858862 |
18157001200 | 0.113149 | 0.0000774852 |
18157001300 | 0.055374 | 0.0001282992 |
18157001400 | 0.146750 | 0.0000881156 |
18157001501 | 0.020183 | 0.0001321871 |
18157001502 | 0.069047 | 0.0001712559 |
18157001600 | 0.172998 | 0.0003112187 |
18157001700 | 0.086825 | 0.0001845236 |
18157001800 | 0.165095 | 0.0001006220 |
18157001900 | 0.118899 | 0.0001234870 |
18157005101 | 0.677626 | 0.0000971148 |
18157005102 | 0.323571 | 0.0001413494 |
18157005200 | 0.105274 | 0.0001570639 |
18157005300 | 0.296601 | 0.0001107903 |
18157005400 | 0.246884 | 0.0002002925 |
18157005500 | 0.408745 | 0.0001277555 |
18157010100 | 0.295012 | 0.0001627190 |
18157010201 | 0.252017 | 0.0001396637 |
18157010203 | 0.249715 | 0.0002909910 |
18157010204 | 0.121393 | 0.0003885952 |
18157010300 | 0.420487 | 0.0000864028 |
18157010400 | 0.301657 | 0.0001627733 |
18157010500 | 0.625663 | 0.0000584266 |
18157010600 | 0.166313 | 0.0001525235 |
18157010700 | 0.035569 | 0.0001511913 |
18157010800 | 0.152116 | 0.0001429262 |
18157010901 | 0.122246 | 0.0002176655 |
18157010902 | 0.274543 | 0.0001189194 |
18157011100 | 0.034724 | 0.0001119050 |
18163000100 | 0.131823 | 0.0000537775 |
18163000201 | 0.128581 | 0.0002000750 |
18163000202 | 0.242679 | 0.0000554087 |
18163000300 | 0.128102 | 0.0000926288 |
18163000400 | 0.227848 | 0.0000605744 |
18163000500 | 0.253896 | 0.0000569312 |
18163000600 | 0.085366 | 0.0000486933 |
18163000800 | 0.065175 | 0.0000813459 |
18163000900 | 0.044262 | 0.0001552423 |
18163001000 | 0.079457 | 0.0001111981 |
18163001100 | 0.087771 | 0.0000672626 |
18163001200 | 0.236962 | 0.0000439627 |
18163001300 | 0.510539 | 0.0000500255 |
18163001400 | 0.088664 | 0.0000432286 |
18163001500 | 0.538042 | 0.0000485574 |
18163001700 | 0.089179 | 0.0000451589 |
18163001800 | 0.222690 | 0.0000180799 |
18163001900 | 0.105385 | 0.0000253662 |
18163002000 | 0.205371 | 0.0000268887 |
18163002100 | 0.158632 | 0.0000580459 |
18163002300 | 0.291923 | 0.0000726186 |
18163002400 | 0.144881 | 0.0000913238 |
18163002500 | 0.103597 | 0.0000429295 |
18163002600 | 0.131402 | 0.0000918404 |
18163002800 | 0.231957 | 0.0000756093 |
18163002900 | 0.243694 | 0.0000297706 |
18163003000 | 0.301198 | 0.0001258523 |
18163003100 | 0.323697 | 0.0000704980 |
18163003200 | 0.156134 | 0.0001075821 |
18163003300 | 0.129508 | 0.0000985558 |
18163003400 | 0.350402 | 0.0000732983 |
18163003500 | 0.121526 | 0.0000871913 |
18163003600 | 0.053791 | 0.0001119593 |
18163003701 | 0.067383 | 0.0000496177 |
18163003702 | 0.075154 | 0.0001265320 |
18163003801 | 0.072428 | 0.0001317521 |
18163003803 | 0.102261 | 0.0001445575 |
18163003804 | 0.075859 | 0.0001577980 |
18163003900 | 0.166151 | 0.0000816721 |
18163010100 | 0.074530 | 0.0001640240 |
18163010201 | 0.163929 | 0.0003130675 |
18163010202 | 0.249022 | 0.0000835481 |
18163010203 | 0.303884 | 0.0002364523 |
18163010403 | 0.219220 | 0.0001739747 |
18163010404 | 0.275251 | 0.0001992050 |
18163010500 | 0.277250 | 0.0002110317 |
18163010700 | 0.220758 | 0.0002386273 |
18163980100 | 0.374206 | 0.0000018760 |
18173030300 | 0.272826 | 0.0001474938 |
18173030400 | 0.369033 | 0.0000706883 |
18173030500 | 0.201004 | 0.0001842517 |
18173030702 | 0.133240 | 0.0001919458 |
18173030703 | 0.230496 | 0.0001515448 |
18173030704 | 0.213318 | 0.0001285439 |
18173030705 | 0.175162 | 0.0002440920 |
18173030800 | 0.187218 | 0.0001806629 |
18183050700 | 0.374206 | 0.0000894207 |
21015070100 | 0.184088 | 0.0001733766 |
21015070200 | 0.056742 | 0.0001797657 |
21015070301 | 0.255559 | 0.0001479288 |
21015070305 | 0.184327 | 0.0001587224 |
21015070307 | 0.302756 | 0.0003272595 |
21015070308 | 0.135269 | 0.0003106750 |
21015070309 | 0.208761 | 0.0001650843 |
21015070311 | 0.189414 | 0.0000748208 |
21015070312 | 0.099920 | 0.0000876263 |
21015070313 | 0.217536 | 0.0000814818 |
21015070314 | 0.240013 | 0.0001298761 |
21015070401 | 0.193419 | 0.0002657335 |
21015070402 | 0.165418 | 0.0002462399 |
21015070502 | 0.323398 | 0.0001308549 |
21015070503 | 0.130213 | 0.0001719356 |
21015070504 | 0.101388 | 0.0002143758 |
21015070601 | 0.316058 | 0.0000730536 |
21015070604 | 0.320366 | 0.0000926832 |
21015070605 | 0.250996 | 0.0001886017 |
21015070606 | 0.329739 | 0.0001168531 |
21015070607 | 0.237747 | 0.0001224538 |
21019030200 | 0.167163 | 0.0000283569 |
21019030300 | 0.162083 | 0.0000498624 |
21019030400 | 0.284053 | 0.0000544843 |
21019030500 | 0.311374 | 0.0001110893 |
21019030600 | 0.294995 | 0.0001006764 |
21019030700 | 0.194533 | 0.0000901547 |
21019030800 | 0.241235 | 0.0001060868 |
21019030900 | 0.244179 | 0.0001422194 |
21019031001 | 0.345692 | 0.0000398573 |
21019031002 | 0.120127 | 0.0001789501 |
21019031100 | 0.338660 | 0.0001992865 |
21019031200 | 0.374206 | 0.0001016552 |
21019031300 | 0.222267 | 0.0000614172 |
21029020101 | 0.304608 | 0.0000972779 |
21029020102 | 0.276988 | 0.0000970876 |
21029020103 | 0.173856 | 0.0000878981 |
21029020201 | 0.249875 | 0.0001699509 |
21029020202 | 0.319102 | 0.0001080171 |
21029020300 | 0.295986 | 0.0001407240 |
21029020400 | 0.312948 | 0.0001838711 |
21029020500 | 0.250416 | 0.0001445575 |
21029020601 | 0.182944 | 0.0001665524 |
21029020602 | 0.303816 | 0.0000380901 |
21029020701 | 0.252930 | 0.0001858286 |
21029020702 | 0.209213 | 0.0000611997 |
21029020800 | 0.252675 | 0.0001355855 |
21029020900 | 0.328749 | 0.0000874903 |
21029021101 | 0.288585 | 0.0001717181 |
21037050100 | 0.147237 | 0.0000398029 |
21037050400 | 0.128407 | 0.0000610638 |
21037050500 | 0.111329 | 0.0000518743 |
21037050600 | 0.063867 | 0.0000502974 |
21037051101 | 0.260743 | 0.0000588616 |
21037051102 | 0.269904 | 0.0000465999 |
21037051200 | 0.194870 | 0.0000306678 |
21037051300 | 0.341339 | 0.0001169347 |
21037051901 | 0.361901 | 0.0001421922 |
21037051903 | 0.320504 | 0.0001599458 |
21037051904 | 0.246289 | 0.0001236501 |
21037052001 | 0.374206 | 0.0001342533 |
21037052100 | 0.304007 | 0.0000945320 |
21037052200 | 0.213708 | 0.0000570672 |
21037052301 | 0.135654 | 0.0001238404 |
21037052302 | 0.238379 | 0.0001333561 |
21037052400 | 0.195569 | 0.0000607647 |
21037052500 | 0.122777 | 0.0001421378 |
21037052800 | 0.294783 | 0.0000894750 |
21037052900 | 0.294352 | 0.0001448838 |
21037053100 | 0.258211 | 0.0001684828 |
21037053200 | 0.057349 | 0.0000933085 |
21037053301 | 0.210565 | 0.0001548073 |
21037053302 | 0.114692 | 0.0001294683 |
21047201301 | 0.174243 | 0.0000780834 |
21047201302 | 0.064583 | 0.0001989331 |
21047201400 | 0.125526 | 0.0000813731 |
21047201501 | 0.111072 | 0.0001180766 |
21047201502 | 0.065567 | 0.0001116875 |
21047201503 | 0.018188 | 0.0001189194 |
21067000101 | 0.033211 | 0.0000832490 |
21067000102 | 0.035706 | 0.0000412439 |
21067000200 | 0.163386 | 0.0000968429 |
21067000300 | 0.259948 | 0.0000692473 |
21067000400 | 0.326252 | 0.0000496177 |
21067000500 | 0.181938 | 0.0000873272 |
21067000600 | 0.299640 | 0.0001199797 |
21067000700 | 0.219731 | 0.0000726730 |
21067000801 | 0.084196 | 0.0000755549 |
21067000802 | 0.055990 | 0.0001215295 |
21067000900 | 0.044280 | 0.0001476841 |
21067001000 | 0.059203 | 0.0000431198 |
21067001100 | 0.548102 | 0.0001240851 |
21067001300 | 0.215572 | 0.0000531521 |
21067001400 | 0.062401 | 0.0000584266 |
21067001500 | 0.069879 | 0.0000612813 |
21067001600 | 0.018110 | 0.0000647070 |
21067001700 | 0.183220 | 0.0000670723 |
21067001800 | 0.185094 | 0.0000793884 |
21067001900 | 0.069311 | 0.0001241667 |
21067002001 | 0.436883 | 0.0001669331 |
21067002002 | 0.288477 | 0.0000651691 |
21067002200 | 0.025062 | 0.0000449958 |
21067002302 | 0.245195 | 0.0001523604 |
21067002303 | 0.055988 | 0.0001153850 |
21067002304 | 0.291206 | 0.0000592150 |
21067002400 | 0.179196 | 0.0001112797 |
21067002500 | 0.160250 | 0.0000929007 |
21067002600 | 0.051048 | 0.0001383859 |
21067002700 | 0.082045 | 0.0001021989 |
21067002800 | 0.207507 | 0.0001062499 |
21067002900 | 0.185213 | 0.0001197622 |
21067003000 | 0.139062 | 0.0001524148 |
21067003101 | 0.050084 | 0.0000682142 |
21067003102 | 0.278929 | 0.0000708242 |
21067003201 | 0.015950 | 0.0000422226 |
21067003202 | 0.066196 | 0.0001637249 |
21067003300 | 0.105999 | 0.0000726458 |
21067003402 | 0.083081 | 0.0001284623 |
21067003404 | 0.100506 | 0.0001183485 |
21067003405 | 0.062563 | 0.0001484726 |
21067003406 | 0.011710 | 0.0001708481 |
21067003407 | 0.072550 | 0.0000981751 |
21067003501 | 0.058761 | 0.0001067937 |
21067003503 | 0.042436 | 0.0000627222 |
21067003504 | 0.136862 | 0.0001041564 |
21067003600 | 0.198083 | 0.0001200885 |
21067003701 | 0.052879 | 0.0000841734 |
21067003702 | 0.031861 | 0.0001296042 |
21067003703 | 0.020956 | 0.0001355312 |
21067003704 | 0.054391 | 0.0001414581 |
21067003802 | 0.169245 | 0.0000567681 |
21067003803 | 0.126422 | 0.0000995073 |
21067003804 | 0.918843 | 0.0001557589 |
21067003906 | 0.117277 | 0.0001297674 |
21067003908 | 0.049009 | 0.0001495873 |
21067003909 | 0.004971 | 0.0000798506 |
21067003910 | 0.167176 | 0.0000684045 |
21067003911 | 0.031795 | 0.0001031777 |
21067003912 | 0.052533 | 0.0001194088 |
21067003913 | 0.107795 | 0.0002202212 |
21067003914 | 0.135402 | 0.0000613900 |
21067003915 | 0.098487 | 0.0001135362 |
21067003916 | 0.307522 | 0.0000150349 |
21067003917 | 0.070462 | 0.0000383348 |
21067003918 | 0.105367 | 0.0000819984 |
21067004001 | 0.024972 | 0.0001710656 |
21067004003 | 0.024985 | 0.0001438234 |
21067004005 | 0.221071 | 0.0000475786 |
21067004006 | 0.266569 | 0.0000303960 |
21067004007 | 0.283403 | 0.0000484487 |
21067004103 | 0.174382 | 0.0000454852 |
21067004104 | 0.033484 | 0.0001184844 |
21067004105 | 0.103854 | 0.0001279186 |
21067004106 | 0.139671 | 0.0001252542 |
21067004107 | 0.147496 | 0.0001379237 |
21067004204 | 0.154073 | 0.0001469500 |
21067004205 | 0.174480 | 0.0001831914 |
21067004207 | 0.100315 | 0.0001050265 |
21067004208 | 0.264546 | 0.0001859917 |
21067004209 | 0.121923 | 0.0001167172 |
21067004210 | 0.135411 | 0.0001408872 |
21089040100 | 0.245549 | 0.0001210129 |
21089040201 | 0.219123 | 0.0000711233 |
21089040202 | 0.356146 | 0.0001100018 |
21089040300 | 0.289510 | 0.0001128022 |
21089040400 | 0.352306 | 0.0001601633 |
21089040501 | 0.334615 | 0.0000828956 |
21089040502 | 0.232787 | 0.0001251454 |
21101020100 | 0.149177 | 0.0000470893 |
21101020200 | 0.047612 | 0.0000471980 |
21101020300 | 0.055727 | 0.0000465183 |
21101020400 | 0.075314 | 0.0000585625 |
21101020500 | 0.184376 | 0.0000630213 |
21101020601 | 0.163433 | 0.0001660902 |
21101020602 | 0.098852 | 0.0001311267 |
21101020701 | 0.125319 | 0.0001551336 |
21101020702 | 0.349527 | 0.0001869977 |
21101020800 | 0.209346 | 0.0001209313 |
21101020900 | 0.202530 | 0.0001838983 |
21111000200 | 0.114895 | 0.0000675073 |
21111000300 | 0.261568 | 0.0000578284 |
21111000400 | 0.936881 | 0.0001129925 |
21111000600 | 1.348193 | 0.0000427120 |
21111000700 | 1.510709 | 0.0000720748 |
21111000800 | 1.660740 | 0.0000519287 |
21111000900 | 1.527004 | 0.0000542125 |
21111001000 | 0.989910 | 0.0000756908 |
21111001100 | 1.612669 | 0.0000843365 |
21111001200 | 1.704981 | 0.0000793340 |
21111001400 | 1.737394 | 0.0000685948 |
21111001500 | 1.597572 | 0.0000736246 |
21111001600 | 1.345835 | 0.0000617163 |
21111001700 | 1.506347 | 0.0000613900 |
21111001800 | 1.742642 | 0.0000343654 |
21111002100 | 0.168555 | 0.0000668276 |
21111002300 | 0.269159 | 0.0000572303 |
21111002400 | 1.414625 | 0.0001373799 |
21111002700 | 1.158701 | 0.0000686220 |
21111002800 | 1.103100 | 0.0000556262 |
21111003000 | 1.324906 | 0.0000775940 |
21111003500 | 0.166449 | 0.0001403434 |
21111003600 | 0.264472 | 0.0001073374 |
21111003700 | 0.230545 | 0.0000422770 |
21111003800 | 0.087432 | 0.0000947767 |
21111003900 | 0.132260 | 0.0000921666 |
21111004000 | 0.027775 | 0.0000417605 |
21111004100 | 0.046104 | 0.0000673714 |
21111004301 | 0.585261 | 0.0001100018 |
21111004302 | 0.034453 | 0.0000324894 |
21111004400 | 0.012094 | 0.0001034496 |
21111004500 | 0.078943 | 0.0000873272 |
21111004600 | 0.136221 | 0.0001087784 |
21111004900 | 0.220021 | 0.0001165269 |
21111005000 | 0.402841 | 0.0000482855 |
21111005100 | 0.078693 | 0.0000716942 |
21111005200 | 0.072406 | 0.0000768599 |
21111005300 | 0.062831 | 0.0000886050 |
21111005600 | 0.305378 | 0.0001009483 |
21111005900 | 0.459512 | 0.0001284895 |
21111006200 | 0.787242 | 0.0000617979 |
21111006300 | 0.137999 | 0.0000428752 |
21111006400 | 0.188528 | 0.0000482583 |
21111006500 | 0.407439 | 0.0000802856 |
21111006600 | 0.078608 | 0.0000496177 |
21111006800 | 0.084945 | 0.0000579100 |
21111006900 | 0.116874 | 0.0000652235 |
21111007000 | 0.199865 | 0.0000594053 |
21111007100 | 0.048831 | 0.0001242210 |
21111007400 | 0.131611 | 0.0000564962 |
21111007501 | 0.263907 | 0.0001471404 |
21111007502 | 0.135374 | 0.0001535839 |
21111007601 | 0.132523 | 0.0000583994 |
21111007602 | 0.069722 | 0.0000931998 |
21111007603 | 0.048870 | 0.0000686220 |
21111007700 | 0.095097 | 0.0000923841 |
21111007800 | 0.171110 | 0.0000837928 |
21111007900 | 0.159555 | 0.0000540493 |
21111008100 | 0.150839 | 0.0000912422 |
21111008200 | 0.096778 | 0.0001120953 |
21111008300 | 0.207323 | 0.0000677248 |
21111008400 | 0.228548 | 0.0000790893 |
21111008500 | 0.300362 | 0.0000553544 |
21111008700 | 0.159400 | 0.0001129925 |
21111008800 | 0.208498 | 0.0000792796 |
21111008900 | 0.228414 | 0.0001318608 |
21111009000 | 0.035672 | 0.0001956706 |
21111009103 | 0.121335 | 0.0000413798 |
21111009105 | 0.078092 | 0.0000616891 |
21111009106 | 0.036484 | 0.0001333833 |
21111009300 | 0.244087 | 0.0001307461 |
21111009400 | 0.262268 | 0.0001606799 |
21111009600 | 0.219512 | 0.0001187835 |
21111009700 | 0.243801 | 0.0000738149 |
21111009800 | 0.293500 | 0.0000702805 |
21111009900 | 0.219694 | 0.0000772405 |
21111010001 | 0.202021 | 0.0001212848 |
21111010004 | 0.011154 | 0.0001279730 |
21111010005 | 0.077767 | 0.0001176688 |
21111010006 | 0.035226 | 0.0000971692 |
21111010007 | 0.096809 | 0.0001174513 |
21111010008 | 0.015894 | 0.0001049721 |
21111010102 | 0.208799 | 0.0001153850 |
21111010103 | 0.029267 | 0.0001074462 |
21111010104 | 0.072627 | 0.0000708786 |
21111010307 | 0.066379 | 0.0002008091 |
21111010309 | 0.094335 | 0.0001247648 |
21111010311 | 0.054217 | 0.0001973834 |
21111010312 | 0.153298 | 0.0000878710 |
21111010313 | 0.140206 | 0.0001369449 |
21111010314 | 0.094200 | 0.0001733766 |
21111010315 | 0.110730 | 0.0000947223 |
21111010316 | 0.108645 | 0.0001272933 |
21111010317 | 0.154023 | 0.0001310724 |
21111010318 | 0.169440 | 0.0001462703 |
21111010319 | 0.006337 | 0.0001149228 |
21111010320 | 0.100531 | 0.0001016552 |
21111010402 | 0.109601 | 0.0001639968 |
21111010403 | 0.161754 | 0.0001047274 |
21111010405 | 0.013113 | 0.0001219373 |
21111010406 | 0.055595 | 0.0001639152 |
21111010500 | 0.155227 | 0.0001009211 |
21111010601 | 0.101265 | 0.0000838744 |
21111010602 | 0.021572 | 0.0001036399 |
21111010701 | 0.190026 | 0.0001388753 |
21111010702 | 0.194416 | 0.0001453188 |
21111010705 | 0.129016 | 0.0001654106 |
21111010706 | 0.273980 | 0.0000840919 |
21111010800 | 0.086688 | 0.0000962448 |
21111010901 | 0.002927 | 0.0001230248 |
21111010902 | 0.073604 | 0.0001103553 |
21111011002 | 0.319729 | 0.0001489619 |
21111011003 | 0.017533 | 0.0001762585 |
21111011004 | 0.007673 | 0.0001787870 |
21111011005 | 0.032810 | 0.0000777571 |
21111011102 | 0.023503 | 0.0001892271 |
21111011106 | 0.019147 | 0.0001929518 |
21111011109 | 0.024077 | 0.0000527171 |
21111011110 | 0.167858 | 0.0001755244 |
21111011111 | 0.027752 | 0.0001435244 |
21111011112 | 0.084785 | 0.0000909704 |
21111011113 | 0.068469 | 0.0000675617 |
21111011114 | 0.054851 | 0.0001437419 |
21111011200 | 0.279136 | 0.0001312627 |
21111011301 | 0.471961 | 0.0000657945 |
21111011302 | 0.967598 | 0.0002173392 |
21111011403 | 0.149110 | 0.0000513306 |
21111011404 | 0.299916 | 0.0000913510 |
21111011405 | 0.376985 | 0.0001498319 |
21111011406 | 0.296708 | 0.0001222091 |
21111011505 | 0.034744 | 0.0001990962 |
21111011506 | 0.038700 | 0.0001406968 |
21111011508 | 0.037960 | 0.0001653834 |
21111011509 | 0.056857 | 0.0001048361 |
21111011513 | 0.065378 | 0.0001056790 |
21111011514 | 0.091954 | 0.0000863484 |
21111011515 | 0.091520 | 0.0001428991 |
21111011516 | 0.072794 | 0.0001144878 |
21111011517 | 0.036088 | 0.0001500223 |
21111011518 | 0.127424 | 0.0000648701 |
21111011519 | 0.090337 | 0.0001425456 |
21111011520 | 0.137792 | 0.0001179407 |
21111011601 | 0.147757 | 0.0002095907 |
21111011603 | 0.119554 | 0.0001274020 |
21111011604 | 0.303540 | 0.0000642448 |
21111011706 | 0.074523 | 0.0000968973 |
21111011707 | 0.026874 | 0.0001813154 |
21111011708 | 0.015319 | 0.0001616043 |
21111011709 | 0.129651 | 0.0001437691 |
21111011710 | 0.084787 | 0.0000769687 |
21111011711 | 0.044261 | 0.0001613324 |
21111011712 | 0.045023 | 0.0001317792 |
21111011713 | 0.067581 | 0.0000683501 |
21111011800 | 0.012758 | 0.0000673442 |
21111011901 | 1.455658 | 0.0000252847 |
21111011904 | 0.100623 | 0.0000662023 |
21111011905 | 0.039041 | 0.0001995856 |
21111011906 | 0.135220 | 0.0000747393 |
21111011907 | 0.041488 | 0.0001294411 |
21111012001 | 0.188819 | 0.0000952389 |
21111012002 | 0.072585 | 0.0001514088 |
21111012003 | 0.092835 | 0.0000797690 |
21111012103 | 0.170161 | 0.0000934173 |
21111012104 | 0.112853 | 0.0000984742 |
21111012105 | 0.060965 | 0.0001275651 |
21111012106 | 0.064572 | 0.0002194055 |
21111012107 | 0.319620 | 0.0001429806 |
21111012202 | 0.003719 | 0.0001726969 |
21111012203 | 0.109852 | 0.0001634802 |
21111012204 | 0.106876 | 0.0001179950 |
21111012301 | 0.072382 | 0.0000907801 |
21111012302 | 0.017546 | 0.0001417844 |
21111012406 | 0.082247 | 0.0001380596 |
21111012407 | 0.085162 | 0.0001302295 |
21111012408 | 0.062171 | 0.0000636194 |
21111012409 | 0.146135 | 0.0000843637 |
21111012410 | 0.087667 | 0.0001106000 |
21111012411 | 0.077320 | 0.0001777266 |
21111012501 | 0.099409 | 0.0000726730 |
21111012502 | 0.040171 | 0.0001439322 |
21111012503 | 0.162136 | 0.0001129109 |
21111012601 | 0.791645 | 0.0001882211 |
21111012603 | 0.286832 | 0.0000866203 |
21111012604 | 0.344777 | 0.0001464335 |
21111012701 | 0.523233 | 0.0000931182 |
21111012702 | 0.056212 | 0.0000514121 |
21111012703 | 0.058035 | 0.0001665253 |
21111012801 | 1.127531 | 0.0000770502 |
21111012802 | 0.640815 | 0.0000625591 |
21111013100 | 0.288194 | 0.0000568225 |
21113060200 | 0.218327 | 0.0001206323 |
21113060600 | 0.256137 | 0.0001850945 |
21117060300 | 0.225405 | 0.0000428480 |
21117060700 | 0.067810 | 0.0000434733 |
21117060900 | 0.049944 | 0.0000650876 |
21117061000 | 0.057373 | 0.0000587528 |
21117061100 | 0.127733 | 0.0000374104 |
21117061200 | 0.234925 | 0.0000625047 |
21117061300 | 0.278139 | 0.0000635651 |
21117061400 | 0.209936 | 0.0000859406 |
21117061600 | 0.060570 | 0.0000303416 |
21117063603 | 0.151181 | 0.0002511881 |
21117063604 | 0.161597 | 0.0001592933 |
21117063605 | 0.313777 | 0.0003251660 |
21117063606 | 0.287328 | 0.0001241123 |
21117063701 | 0.324564 | 0.0000899372 |
21117063702 | 0.322745 | 0.0001197894 |
21117063800 | 0.186930 | 0.0000676432 |
21117064000 | 0.233602 | 0.0001630724 |
21117064100 | 0.254013 | 0.0001582058 |
21117064200 | 0.226890 | 0.0000405642 |
21117064300 | 0.146394 | 0.0000769687 |
21117064400 | 0.059240 | 0.0000899644 |
21117064500 | 0.230807 | 0.0000900188 |
21117064600 | 0.175926 | 0.0001411590 |
21117064700 | 0.326127 | 0.0001404250 |
21117064800 | 0.123949 | 0.0000905354 |
21117064900 | 0.142910 | 0.0000747121 |
21117065000 | 0.062917 | 0.0001001055 |
21117065100 | 0.087816 | 0.0000864572 |
21117065200 | 0.199856 | 0.0001152491 |
21117065300 | 0.203531 | 0.0002924863 |
21117065400 | 0.129963 | 0.0000447783 |
21117065501 | 0.256615 | 0.0001230248 |
21117065502 | 0.298124 | 0.0001064402 |
21117065600 | 0.104491 | 0.0001722347 |
21117065700 | 0.231266 | 0.0000519015 |
21117065800 | 0.374206 | 0.0000871097 |
21117065900 | 0.303026 | 0.0000405642 |
21117066800 | 0.228369 | 0.0002214446 |
21117066900 | 0.183131 | 0.0001177775 |
21117067000 | 0.055199 | 0.0000806934 |
21117067100 | 0.447588 | 0.0000622872 |
21185030200 | 0.088050 | 0.0001163366 |
21185030301 | 0.078189 | 0.0000972507 |
21185030302 | 0.128871 | 0.0001176960 |
21185030401 | 0.189759 | 0.0001885202 |
21185030402 | 0.261610 | 0.0000809924 |
21185030501 | 0.171205 | 0.0001050265 |
21185030502 | 0.204192 | 0.0001434156 |
21185030601 | 0.148341 | 0.0001718269 |
21185030602 | 0.171885 | 0.0001442584 |
21185030701 | 0.210336 | 0.0000714495 |
21185030702 | 0.189682 | 0.0001845236 |
21185030801 | 0.165455 | 0.0001184029 |
21185030802 | 0.213845 | 0.0001403434 |
21209040203 | 0.156322 | 0.0001164725 |
21209040205 | 0.145738 | 0.0001251726 |
21209040601 | 0.157581 | 0.0001028786 |
21211040502 | 0.091234 | 0.0001867258 |
21219950400 | 0.095079 | 0.0000376279 |
39007000900 | 0.102766 | 0.0001210401 |
39017000100 | 0.086932 | 0.0001364556 |
39017000200 | 0.148365 | 0.0000996161 |
39017000300 | 0.302892 | 0.0000790621 |
39017000400 | 0.160128 | 0.0001209585 |
39017000500 | 0.077294 | 0.0001170978 |
39017000600 | 0.070064 | 0.0001299849 |
39017001001 | 0.253658 | 0.0001497504 |
39017001002 | 0.269640 | 0.0001354224 |
39017001100 | 0.141920 | 0.0001128565 |
39017001300 | 0.240489 | 0.0001252542 |
39017010301 | 0.326793 | 0.0001199797 |
39017010500 | 0.202960 | 0.0000687851 |
39017010600 | 0.322926 | 0.0000991539 |
39017010800 | 0.340072 | 0.0001797385 |
39017010901 | 0.092335 | 0.0001157656 |
39017010903 | 0.237664 | 0.0001340086 |
39017010904 | 0.121709 | 0.0000933085 |
39017010906 | 0.134115 | 0.0001964862 |
39017010907 | 0.070754 | 0.0000695464 |
39017010908 | 0.040756 | 0.0001479288 |
39017010909 | 0.152615 | 0.0001278642 |
39017010910 | 0.066045 | 0.0001288973 |
39017010911 | 0.144108 | 0.0001029058 |
39017011002 | 0.074657 | 0.0003314736 |
39017011003 | 0.181951 | 0.0001769382 |
39017011004 | 0.010576 | 0.0001702500 |
39017011109 | 0.039598 | 0.0001296858 |
39017011110 | 0.240461 | 0.0001444216 |
39017011111 | 0.142348 | 0.0001770197 |
39017011112 | 0.111091 | 0.0001693800 |
39017011116 | 0.113199 | 0.0002291387 |
39017011117 | 0.060406 | 0.0003210879 |
39017011118 | 0.131932 | 0.0000849075 |
39017011120 | 0.106117 | 0.0001887105 |
39017011121 | 0.116621 | 0.0002108142 |
39017011122 | 0.258467 | 0.0001510826 |
39017011123 | 0.184915 | 0.0001265592 |
39017011125 | 0.125525 | 0.0001007852 |
39017011126 | 0.062703 | 0.0001238676 |
39017011127 | 0.070486 | 0.0001253901 |
39017011128 | 0.063915 | 0.0000850706 |
39017011129 | 0.039923 | 0.0001054615 |
39017011130 | 0.086474 | 0.0001444488 |
39017011131 | 0.171969 | 0.0000856959 |
39017011200 | 0.191881 | 0.0002118745 |
39017011300 | 0.107989 | 0.0001695159 |
39017014000 | 0.147852 | 0.0000664198 |
39017014100 | 0.123938 | 0.0000584266 |
39017014600 | 0.062301 | 0.0000247409 |
39017014700 | 0.060391 | 0.0001018183 |
39017014800 | 0.194407 | 0.0001884658 |
39017014900 | 0.274941 | 0.0001451285 |
39017015000 | 0.318761 | 0.0002002925 |
39023002701 | 0.230267 | 0.0000786815 |
39023002702 | 0.197973 | 0.0000691658 |
39023002800 | 0.235169 | 0.0001176144 |
39023002901 | 0.228690 | 0.0000931182 |
39023002902 | 0.254094 | 0.0001201429 |
39023003001 | 0.170496 | 0.0000820256 |
39023003002 | 0.291018 | 0.0000958370 |
39023003101 | 0.358961 | 0.0000700630 |
39023003102 | 0.326959 | 0.0000422770 |
39025040202 | 0.256939 | 0.0000619066 |
39025040203 | 0.293372 | 0.0001744369 |
39025040204 | 0.230453 | 0.0001878949 |
39025040301 | 0.213823 | 0.0000993170 |
39025040302 | 0.223426 | 0.0001001327 |
39025040303 | 0.162066 | 0.0002012984 |
39025040401 | 0.260214 | 0.0000938523 |
39025040403 | 0.146937 | 0.0000810196 |
39025040404 | 0.236847 | 0.0001024980 |
39025040405 | 0.210425 | 0.0000778658 |
39025040500 | 0.187970 | 0.0001391471 |
39025040600 | 0.282568 | 0.0001960512 |
39025040701 | 0.179086 | 0.0001935499 |
39025040702 | 0.235099 | 0.0000983111 |
39025040800 | 0.300314 | 0.0001636162 |
39025040900 | 0.337758 | 0.0001585049 |
39025041000 | 0.249064 | 0.0002060563 |
39025041101 | 0.232973 | 0.0000696008 |
39025041102 | 0.233263 | 0.0001408328 |
39025041103 | 0.315079 | 0.0002248159 |
39025041200 | 0.253198 | 0.0002316128 |
39025041303 | 0.184471 | 0.0001355040 |
39025041305 | 0.184547 | 0.0001349330 |
39025041306 | 0.183178 | 0.0001253086 |
39025041307 | 0.251060 | 0.0001257979 |
39025041403 | 0.286667 | 0.0001142159 |
39025041404 | 0.213465 | 0.0001330027 |
39025041405 | 0.290744 | 0.0001403162 |
39025041406 | 0.231996 | 0.0001302839 |
39025041501 | 0.245083 | 0.0001869433 |
39025041502 | 0.258277 | 0.0002127445 |
39025041600 | 0.241568 | 0.0001440409 |
39025041701 | 0.234179 | 0.0001119050 |
39025041900 | 0.256399 | 0.0001573358 |
39035101101 | 0.269495 | 0.0000541581 |
39035101102 | 0.070582 | 0.0001184572 |
39035101200 | 0.214086 | 0.0000760986 |
39035101300 | 0.122170 | 0.0000489924 |
39035101400 | 0.224437 | 0.0000529618 |
39035101501 | 0.093366 | 0.0000575022 |
39035101603 | 0.135894 | 0.0000682686 |
39035101700 | 0.327228 | 0.0000707426 |
39035101800 | 0.212080 | 0.0000712592 |
39035101901 | 0.327368 | 0.0000412439 |
39035102101 | 0.205576 | 0.0000834937 |
39035102102 | 0.122842 | 0.0000685676 |
39035102200 | 0.220999 | 0.0000781649 |
39035102300 | 0.305105 | 0.0000556806 |
39035102401 | 0.131105 | 0.0000537503 |
39035102402 | 0.238837 | 0.0000999423 |
39035102700 | 0.279481 | 0.0001064130 |
39035102800 | 0.551474 | 0.0000507052 |
39035102900 | 0.456371 | 0.0000517384 |
39035103100 | 0.048636 | 0.0000322719 |
39035103300 | 0.606640 | 0.0000644895 |
39035103400 | 0.120037 | 0.0000624776 |
39035103500 | 0.031411 | 0.0000399117 |
39035103602 | 0.007718 | 0.0000871641 |
39035103800 | 0.396222 | 0.0000392592 |
39035103900 | 0.429223 | 0.0000597316 |
39035104100 | 0.137267 | 0.0000252031 |
39035104200 | 0.074567 | 0.0000349363 |
39035104300 | 0.054484 | 0.0000558709 |
39035104400 | 0.030328 | 0.0000317553 |
39035104600 | 0.644776 | 0.0000274053 |
39035104800 | 0.066799 | 0.0000453221 |
39035104900 | 0.616764 | 0.0000616347 |
39035105100 | 0.302940 | 0.0001137266 |
39035105300 | 0.590450 | 0.0000869738 |
39035105400 | 0.190509 | 0.0000857775 |
39035105500 | 0.490312 | 0.0000610366 |
39035105602 | 0.336175 | 0.0000697367 |
39035105700 | 0.054436 | 0.0001025796 |
39035105900 | 0.085424 | 0.0000838744 |
39035106100 | 0.085849 | 0.0000988005 |
39035106200 | 0.171990 | 0.0001024164 |
39035106300 | 0.071705 | 0.0000695736 |
39035106400 | 0.155310 | 0.0000284656 |
39035106500 | 0.105821 | 0.0000685132 |
39035106600 | 0.032730 | 0.0000866475 |
39035106800 | 0.187352 | 0.0000782465 |
39035106900 | 0.033493 | 0.0000900732 |
39035107000 | 0.064461 | 0.0000441802 |
39035107101 | 0.201481 | 0.0001291148 |
39035107701 | 0.046896 | 0.0000880613 |
39035107802 | 0.346727 | 0.0001023077 |
39035108201 | 0.094377 | 0.0000421955 |
39035108301 | 0.390674 | 0.0000335497 |
39035108400 | 0.859757 | 0.0000331147 |
39035108701 | 1.493389 | 0.0001200885 |
39035109301 | 1.070717 | 0.0000283297 |
39035109701 | 0.927364 | 0.0000632388 |
39035109801 | 1.695033 | 0.0000626407 |
39035110501 | 0.250731 | 0.0000181343 |
39035110801 | 0.138632 | 0.0000255293 |
39035110901 | 0.153391 | 0.0000810740 |
39035111202 | 0.535051 | 0.0000280306 |
39035111401 | 1.718041 | 0.0000325166 |
39035111500 | 0.512182 | 0.0000267800 |
39035111600 | 1.127800 | 0.0000233815 |
39035111700 | 0.921501 | 0.0000350451 |
39035111800 | 1.560373 | 0.0000171011 |
39035111902 | 1.580360 | 0.0000172099 |
39035112100 | 1.483839 | 0.0000367579 |
39035112200 | 1.690064 | 0.0000331963 |
39035112301 | 1.033146 | 0.0000391776 |
39035112400 | 1.539584 | 0.0000319457 |
39035112500 | 1.420451 | 0.0000351810 |
39035112600 | 1.737225 | 0.0000223484 |
39035112800 | 1.624651 | 0.0000261275 |
39035113101 | 1.041052 | 0.0000178352 |
39035113500 | 1.571672 | 0.0000229193 |
39035113600 | 1.484079 | 0.0000216687 |
39035113801 | 1.431451 | 0.0000460289 |
39035114100 | 1.784406 | 0.0000243059 |
39035114300 | 1.760569 | 0.0000434733 |
39035114501 | 1.484822 | 0.0000192218 |
39035114600 | 0.506553 | 0.0000256925 |
39035114700 | 1.819540 | 0.0000154699 |
39035114900 | 0.531014 | 0.0000442345 |
39035115100 | 0.298652 | 0.0000349635 |
39035115200 | 0.507385 | 0.0000215599 |
39035115300 | 0.614810 | 0.0000229737 |
39035115400 | 0.425653 | 0.0000558981 |
39035115700 | 0.423495 | 0.0000376823 |
39035115800 | 0.414841 | 0.0000774037 |
39035115900 | 0.432658 | 0.0000819984 |
39035116100 | 1.679945 | 0.0000242787 |
39035116200 | 1.661162 | 0.0000187868 |
39035116300 | 1.728944 | 0.0000364588 |
39035116400 | 1.693619 | 0.0000582634 |
39035116500 | 1.658814 | 0.0000615260 |
39035116600 | 1.638222 | 0.0000528259 |
39035116700 | 1.725802 | 0.0000358607 |
39035116800 | 1.545582 | 0.0000552456 |
39035116900 | 1.669240 | 0.0000355616 |
39035117101 | 0.982760 | 0.0000512762 |
39035117102 | 1.487103 | 0.0000282753 |
39035117201 | 0.862518 | 0.0000736246 |
39035117202 | 1.005843 | 0.0000455396 |
39035117300 | 1.260171 | 0.0000648429 |
39035117400 | 1.099843 | 0.0000375735 |
39035117500 | 1.246188 | 0.0000627222 |
39035117600 | 0.886483 | 0.0000917316 |
39035117700 | 0.349694 | 0.0001317249 |
39035117800 | 1.080610 | 0.0000578828 |
39035117900 | 1.480048 | 0.0000596500 |
39035118101 | 1.542110 | 0.0000445880 |
39035118200 | 1.819540 | 0.0000531250 |
39035118301 | 1.322649 | 0.0000685676 |
39035118400 | 1.602146 | 0.0000320000 |
39035118500 | 1.748118 | 0.0000217502 |
39035118602 | 1.489669 | 0.0000524724 |
39035118700 | 0.148628 | 0.0000994530 |
39035118800 | 0.298818 | 0.0000721292 |
39035118900 | 0.782495 | 0.0000354801 |
39035119100 | 0.652692 | 0.0000026916 |
39035119202 | 0.576554 | 0.0000245778 |
39035119300 | 1.588566 | 0.0001025796 |
39035119401 | 0.932593 | 0.0000628310 |
39035119402 | 1.717356 | 0.0000411351 |
39035119501 | 0.334488 | 0.0000599763 |
39035119502 | 0.938835 | 0.0000514393 |
39035119600 | 1.526112 | 0.0000456755 |
39035119701 | 1.538969 | 0.0000530706 |
39035119702 | 1.591584 | 0.0000456755 |
39035119800 | 1.544277 | 0.0000778658 |
39035119900 | 1.561533 | 0.0000484487 |
39035120200 | 1.513183 | 0.0000564419 |
39035120400 | 1.596251 | 0.0000613629 |
39035120500 | 1.702486 | 0.0000496177 |
39035120600 | 1.699070 | 0.0000668548 |
39035120701 | 1.547818 | 0.0000345557 |
39035120702 | 1.734727 | 0.0000460833 |
39035120801 | 1.683851 | 0.0000602753 |
39035120802 | 1.676841 | 0.0000575294 |
39035121100 | 1.803016 | 0.0000573391 |
39035121200 | 1.806253 | 0.0000355616 |
39035121300 | 1.554883 | 0.0000541853 |
39035121401 | 1.757188 | 0.0000538046 |
39035121403 | 1.648826 | 0.0000615532 |
39035121500 | 1.552631 | 0.0000648157 |
39035121700 | 1.749438 | 0.0001202516 |
39035121800 | 1.819540 | 0.0000388242 |
39035121900 | 1.396788 | 0.0000329788 |
39035122100 | 1.395746 | 0.0000915957 |
39035122200 | 1.602257 | 0.0000474971 |
39035122300 | 1.637517 | 0.0000442074 |
39035123100 | 0.290444 | 0.0000661207 |
39035123200 | 0.136559 | 0.0000731624 |
39035123400 | 0.141478 | 0.0000998608 |
39035123501 | 0.084329 | 0.0000965167 |
39035123502 | 0.070533 | 0.0000685132 |
39035123601 | 0.060744 | 0.0000838200 |
39035123602 | 0.138462 | 0.0000701717 |
39035123603 | 0.044485 | 0.0000829500 |
39035123700 | 0.035440 | 0.0000703076 |
39035123800 | 0.513479 | 0.0000685676 |
39035123900 | 0.153385 | 0.0000791437 |
39035124100 | 0.148709 | 0.0001546714 |
39035124201 | 0.029913 | 0.0000612269 |
39035124202 | 0.025145 | 0.0000438267 |
39035124300 | 0.079946 | 0.0001144062 |
39035124500 | 0.015806 | 0.0001024980 |
39035124600 | 0.027389 | 0.0000934716 |
39035126100 | 1.302843 | 0.0000749024 |
39035127501 | 1.473326 | 0.0000757452 |
39035130103 | 0.193558 | 0.0001194632 |
39035130104 | 0.269464 | 0.0001088599 |
39035130105 | 0.277951 | 0.0000910791 |
39035130106 | 0.214667 | 0.0000873816 |
39035131102 | 0.126869 | 0.0000873544 |
39035131103 | 0.109761 | 0.0001129925 |
39035131104 | 0.261945 | 0.0001118778 |
39035132100 | 0.564758 | 0.0001152491 |
39035132200 | 0.375803 | 0.0000897741 |
39035132301 | 0.519701 | 0.0000804215 |
39035132302 | 0.250552 | 0.0000502159 |
39035133103 | 1.063862 | 0.0000899916 |
39035133104 | 0.809379 | 0.0000642176 |
39035134100 | 0.049550 | 0.0000358063 |
39035134203 | 0.127689 | 0.0000896925 |
39035134204 | 0.122757 | 0.0001111981 |
39035134205 | 0.170693 | 0.0000645438 |
39035134206 | 0.166613 | 0.0000770502 |
39035134300 | 0.091929 | 0.0001163094 |
39035135103 | 0.228589 | 0.0000547018 |
39035135104 | 0.231063 | 0.0001164725 |
39035135105 | 0.162930 | 0.0001521157 |
39035135106 | 0.278180 | 0.0000390689 |
39035136101 | 0.206917 | 0.0001625558 |
39035136102 | 0.116570 | 0.0001961600 |
39035136103 | 0.226542 | 0.0001520070 |
39035137101 | 0.024796 | 0.0000595957 |
39035137102 | 0.016755 | 0.0001169619 |
39035137103 | 0.038824 | 0.0001038846 |
39035138105 | 0.071765 | 0.0000322175 |
39035138106 | 0.064727 | 0.0000878981 |
39035138107 | 0.041342 | 0.0000545115 |
39035138108 | 0.190841 | 0.0000994530 |
39035138109 | 0.157201 | 0.0001037214 |
39035138110 | 0.178115 | 0.0001121768 |
39035140100 | 1.138155 | 0.0000372745 |
39035140301 | 1.639266 | 0.0000651963 |
39035140302 | 0.831430 | 0.0000624232 |
39035140400 | 0.457339 | 0.0000813187 |
39035140500 | 0.737871 | 0.0000897197 |
39035140600 | 0.189076 | 0.0000269975 |
39035140701 | 0.659601 | 0.0000674801 |
39035140702 | 0.584288 | 0.0000447783 |
39035140800 | 0.124903 | 0.0001011114 |
39035140900 | 0.407660 | 0.0000554087 |
39035141000 | 0.436201 | 0.0000219677 |
39035141100 | 0.187577 | 0.0001042380 |
39035141200 | 0.100272 | 0.0000754189 |
39035141300 | 0.140573 | 0.0000741139 |
39035141400 | 0.128662 | 0.0000676704 |
39035141500 | 0.028951 | 0.0000433917 |
39035141601 | 0.036321 | 0.0000403195 |
39035141602 | 0.480698 | 0.0000343654 |
39035141700 | 0.076806 | 0.0000350451 |
39035150100 | 1.819540 | 0.0000609007 |
39035150300 | 1.359404 | 0.0000346101 |
39035150400 | 1.690615 | 0.0000453764 |
39035151100 | 1.589076 | 0.0000347460 |
39035151200 | 1.609195 | 0.0000480952 |
39035151300 | 0.951244 | 0.0000540765 |
39035151400 | 1.442696 | 0.0000320544 |
39035151500 | 1.420705 | 0.0000288191 |
39035151600 | 1.246376 | 0.0000455124 |
39035151700 | 1.051011 | 0.0000251487 |
39035151800 | 1.746333 | 0.0000478233 |
39035152101 | 0.136337 | 0.0000644351 |
39035152102 | 0.439346 | 0.0001072015 |
39035152201 | 0.995345 | 0.0000910519 |
39035152202 | 0.665314 | 0.0001149772 |
39035152301 | 0.424857 | 0.0000612541 |
39035152302 | 0.283852 | 0.0001067121 |
39035152303 | 0.244927 | 0.0000914869 |
39035152400 | 0.601688 | 0.0000529618 |
39035152501 | 0.507489 | 0.0001005405 |
39035152502 | 0.632416 | 0.0000592966 |
39035152603 | 1.196125 | 0.0000275684 |
39035152604 | 0.631138 | 0.0001052440 |
39035152701 | 1.467021 | 0.0000603025 |
39035152702 | 0.975745 | 0.0000568225 |
39035152703 | 0.501071 | 0.0000459474 |
39035153103 | 0.189536 | 0.0000606288 |
39035153104 | 0.220266 | 0.0000789534 |
39035153105 | 0.150366 | 0.0000965439 |
39035153106 | 0.225984 | 0.0001044283 |
39035153107 | 0.104665 | 0.0000949398 |
39035154100 | 0.479177 | 0.0000546203 |
39035154200 | 0.315942 | 0.0000356976 |
39035154300 | 1.701884 | 0.0000267800 |
39035154400 | 0.170073 | 0.0000707970 |
39035154501 | 0.135337 | 0.0000896110 |
39035154502 | 0.326357 | 0.0000698454 |
39035154601 | 0.214179 | 0.0001278370 |
39035154603 | 0.189466 | 0.0000809924 |
39035154604 | 0.282252 | 0.0001172882 |
39035154700 | 1.436794 | 0.0000612813 |
39035155101 | 0.253113 | 0.0001455363 |
39035155102 | 0.336441 | 0.0000792252 |
39035156101 | 0.228660 | 0.0000356432 |
39035156102 | 0.268719 | 0.0001564658 |
39035160100 | 0.225723 | 0.0000472524 |
39035160200 | 0.094760 | 0.0000590519 |
39035160300 | 0.169047 | 0.0000453221 |
39035160400 | 0.175859 | 0.0000871097 |
39035160500 | 0.136791 | 0.0001029330 |
39035160601 | 0.044248 | 0.0001248192 |
39035160602 | 0.028786 | 0.0000733255 |
39035160700 | 0.228190 | 0.0000442345 |
39035160800 | 0.276670 | 0.0000252031 |
39035160900 | 0.171502 | 0.0000964895 |
39035161000 | 0.111862 | 0.0000441258 |
39035161100 | 0.187575 | 0.0000949942 |
39035161200 | 0.178128 | 0.0000705795 |
39035161300 | 0.086975 | 0.0000783552 |
39035161400 | 0.117479 | 0.0000856959 |
39035161500 | 0.142665 | 0.0001008939 |
39035161600 | 0.034820 | 0.0000484758 |
39035161700 | 0.020734 | 0.0000565778 |
39035161800 | 0.127523 | 0.0000346916 |
39035170101 | 0.034173 | 0.0000694648 |
39035170102 | 0.171431 | 0.0001279730 |
39035170201 | 0.084561 | 0.0000622057 |
39035170202 | 0.124680 | 0.0001019542 |
39035171102 | 0.979940 | 0.0001328939 |
39035171103 | 0.968962 | 0.0000890400 |
39035171104 | 1.374347 | 0.0001167444 |
39035171203 | 0.725314 | 0.0000680239 |
39035171204 | 0.758096 | 0.0000527443 |
39035171205 | 0.741885 | 0.0000745218 |
39035171206 | 0.307224 | 0.0000616891 |
39035172101 | 0.056966 | 0.0000676976 |
39035172102 | 0.086227 | 0.0000902091 |
39035172103 | 0.182426 | 0.0001231063 |
39035172201 | 0.107835 | 0.0000941242 |
39035172202 | 0.032125 | 0.0001243026 |
39035173103 | 0.085289 | 0.0000710961 |
39035173104 | 0.111944 | 0.0001250639 |
39035173105 | 0.193497 | 0.0000620697 |
39035173106 | 0.503312 | 0.0000974683 |
39035173107 | 0.215217 | 0.0000651148 |
39035174103 | 0.221303 | 0.0000796331 |
39035174104 | 0.163218 | 0.0000637554 |
39035174105 | 0.184791 | 0.0000763977 |
39035174106 | 0.252851 | 0.0000769687 |
39035174107 | 0.255938 | 0.0000899644 |
39035174203 | 0.245895 | 0.0000760171 |
39035174204 | 0.211074 | 0.0000913238 |
39035174205 | 0.116509 | 0.0001395006 |
39035174206 | 0.146338 | 0.0000630485 |
39035174207 | 0.107176 | 0.0000855056 |
39035175103 | 0.184641 | 0.0001912661 |
39035175104 | 0.165945 | 0.0001507020 |
39035175105 | 0.265336 | 0.0001243570 |
39035175106 | 0.307669 | 0.0000820256 |
39035175201 | 0.198826 | 0.0001732135 |
39035175202 | 0.209150 | 0.0000873816 |
39035176100 | 0.228087 | 0.0000615532 |
39035176200 | 0.259703 | 0.0001475210 |
39035177101 | 0.016762 | 0.0001117690 |
39035177103 | 0.073360 | 0.0001052440 |
39035177104 | 0.205330 | 0.0000877078 |
39035177201 | 0.164408 | 0.0001048633 |
39035177202 | 0.258676 | 0.0000812371 |
39035177302 | 0.181638 | 0.0000659304 |
39035177303 | 0.085727 | 0.0001180766 |
39035177304 | 0.029495 | 0.0001014377 |
39035177403 | 0.245967 | 0.0000792796 |
39035177404 | 0.156358 | 0.0000713136 |
39035177405 | 0.172546 | 0.0001236501 |
39035177406 | 0.188413 | 0.0001057605 |
39035177501 | 0.186258 | 0.0001056246 |
39035177503 | 0.207867 | 0.0000893119 |
39035177504 | 0.253155 | 0.0001060052 |
39035177505 | 0.217574 | 0.0001177503 |
39035177604 | 0.249907 | 0.0000558165 |
39035177605 | 0.115965 | 0.0000670451 |
39035177606 | 0.056421 | 0.0001059780 |
39035177607 | 0.171035 | 0.0001018727 |
39035177608 | 0.207724 | 0.0001418115 |
39035177609 | 0.235986 | 0.0000493730 |
39035178101 | 0.188797 | 0.0000711777 |
39035178102 | 0.007958 | 0.0001192457 |
39035178201 | 0.140797 | 0.0000828684 |
39035178204 | 0.031228 | 0.0001235142 |
39035178205 | 0.122975 | 0.0000524724 |
39035178206 | 0.209833 | 0.0000770774 |
39035179101 | 0.203869 | 0.0000890944 |
39035179102 | 0.162853 | 0.0000749839 |
39035180102 | 0.283691 | 0.0001078540 |
39035180103 | 0.375883 | 0.0000916229 |
39035180104 | 0.742270 | 0.0000731080 |
39035181100 | 0.280176 | 0.0001743282 |
39035181201 | 0.206412 | 0.0001501310 |
39035181203 | 0.343572 | 0.0000783009 |
39035181204 | 0.170474 | 0.0001326493 |
39035182103 | 0.219163 | 0.0000643807 |
39035182104 | 0.192410 | 0.0000719933 |
39035182105 | 0.239806 | 0.0000943688 |
39035182106 | 0.268346 | 0.0000825150 |
39035183100 | 0.117580 | 0.0000729992 |
39035183200 | 0.151344 | 0.0000655770 |
39035183300 | 0.105704 | 0.0001099203 |
39035183401 | 0.134621 | 0.0000535871 |
39035183402 | 1.013743 | 0.0000402923 |
39035183501 | 0.266319 | 0.0000788174 |
39035183502 | 0.038039 | 0.0000959729 |
39035183603 | 1.480717 | 0.0000357520 |
39035183604 | 0.640933 | 0.0000542940 |
39035183605 | 0.354332 | 0.0000615532 |
39035183606 | 0.367620 | 0.0000459746 |
39035184103 | 0.134603 | 0.0001026067 |
39035184104 | 0.066392 | 0.0000488293 |
39035184105 | 0.088218 | 0.0001212848 |
39035184106 | 0.070621 | 0.0000585625 |
39035184108 | 0.194687 | 0.0001933596 |
39035185101 | 1.121928 | 0.0000652779 |
39035185102 | 0.222589 | 0.0000614716 |
39035185103 | 0.273841 | 0.0000586169 |
39035185104 | 0.189494 | 0.0001024436 |
39035185201 | 0.720773 | 0.0000442889 |
39035185202 | 0.499206 | 0.0001140800 |
39035185203 | 0.013157 | 0.0001042380 |
39035186103 | 0.189720 | 0.0001208226 |
39035186104 | 0.212342 | 0.0000755277 |
39035186105 | 0.244690 | 0.0000940698 |
39035186106 | 0.045777 | 0.0001283808 |
39035186107 | 0.287998 | 0.0001684012 |
39035186201 | 0.156391 | 0.0001571455 |
39035186202 | 0.166840 | 0.0001150859 |
39035186203 | 0.220248 | 0.0000959185 |
39035186205 | 0.213265 | 0.0001320783 |
39035186206 | 0.255138 | 0.0001030417 |
39035187103 | 0.573464 | 0.0000697911 |
39035187104 | 0.126610 | 0.0000772677 |
39035187105 | 0.018588 | 0.0000811556 |
39035187106 | 0.074799 | 0.0001167988 |
39035188103 | 1.476217 | 0.0000874088 |
39035188104 | 1.471415 | 0.0000499168 |
39035188105 | 1.517557 | 0.0000873816 |
39035188106 | 1.722443 | 0.0000616075 |
39035188107 | 1.307604 | 0.0000658488 |
39035189105 | 0.244264 | 0.0000988276 |
39035189107 | 0.203241 | 0.0001303655 |
39035189108 | 0.177724 | 0.0001316433 |
39035189109 | 0.079313 | 0.0000971420 |
39035189110 | 0.075394 | 0.0001153034 |
39035189111 | 0.186432 | 0.0001836264 |
39035189112 | 0.253329 | 0.0000937435 |
39035190502 | 0.298366 | 0.0000575838 |
39035190503 | 0.182839 | 0.0000433645 |
39035190504 | 0.157513 | 0.0002875653 |
39035192300 | 0.188319 | 0.0000436092 |
39035192800 | 0.110771 | 0.0000368938 |
39035192900 | 0.301859 | 0.0000539678 |
39035193800 | 0.977782 | 0.0000296619 |
39035193900 | 1.223047 | 0.0000227562 |
39035194100 | 0.079626 | 0.0000603841 |
39035194300 | 0.229732 | 0.0000912966 |
39035194500 | 0.174777 | 0.0000584538 |
39035194800 | 0.328321 | 0.0000179168 |
39035194900 | 0.039349 | 0.0000874903 |
39035195600 | 0.985102 | 0.0001292780 |
39035195700 | 0.490156 | 0.0001232423 |
39035195800 | 0.093405 | 0.0000999423 |
39035195900 | 0.286852 | 0.0001110350 |
39035196000 | 0.552232 | 0.0000430655 |
39035196100 | 0.058339 | 0.0000629669 |
39035196200 | 1.544970 | 0.0000993170 |
39035196300 | 0.231458 | 0.0001052711 |
39035196400 | 0.665047 | 0.0000805031 |
39035196500 | 1.610675 | 0.0000398845 |
39041010100 | 0.064327 | 0.0001511370 |
39041010200 | 0.143278 | 0.0001489891 |
39041010420 | 0.222987 | 0.0000762890 |
39041010421 | 0.178258 | 0.0000651691 |
39041010422 | 0.175438 | 0.0001610605 |
39041010520 | 0.148984 | 0.0001773732 |
39041010530 | 0.075107 | 0.0000997248 |
39041011101 | 0.361895 | 0.0000800409 |
39041011102 | 0.287294 | 0.0001585049 |
39041011200 | 0.263508 | 0.0000943688 |
39041011411 | 0.220724 | 0.0000931454 |
39041011412 | 0.126219 | 0.0001357215 |
39041011413 | 0.202037 | 0.0002008091 |
39041011421 | 0.210614 | 0.0001844692 |
39041011423 | 0.231570 | 0.0001682653 |
39041011430 | 0.161849 | 0.0000756093 |
39041011520 | 0.086703 | 0.0000995617 |
39041011530 | 0.295880 | 0.0001133731 |
39041011540 | 0.163976 | 0.0001716909 |
39041011550 | 0.189617 | 0.0003075212 |
39041011560 | 0.218494 | 0.0002372407 |
39041011561 | 0.350782 | 0.0001219916 |
39041011604 | 0.206452 | 0.0001748447 |
39041011710 | 0.183819 | 0.0001765032 |
39041011730 | 0.118094 | 0.0002054582 |
39041011740 | 0.106699 | 0.0001619577 |
39041011750 | 0.184395 | 0.0002062194 |
39041011760 | 0.241177 | 0.0001350962 |
39041011762 | 0.203942 | 0.0001592389 |
39041011900 | 0.196111 | 0.0001492882 |
39041012000 | 0.255873 | 0.0001644046 |
39041012100 | 0.245575 | 0.0002399867 |
39041012200 | 0.181266 | 0.0001405881 |
39041012300 | 0.230133 | 0.0001307189 |
39041012400 | 0.263071 | 0.0001532576 |
39043040100 | 0.271016 | 0.0001496960 |
39043040200 | 0.281345 | 0.0001023892 |
39045030400 | 0.244968 | 0.0001287614 |
39045030600 | 0.048177 | 0.0002949604 |
39045030700 | 0.293345 | 0.0001043740 |
39045032701 | 0.088070 | 0.0001098659 |
39045032702 | 0.205897 | 0.0002179102 |
39045032800 | 0.070121 | 0.0001106543 |
39045032900 | 0.078291 | 0.0002782671 |
39045033000 | 0.099309 | 0.0001261786 |
39045033100 | 0.072992 | 0.0002405848 |
39049000110 | 0.193566 | 0.0000933085 |
39049000120 | 0.238078 | 0.0000855872 |
39049000210 | 0.155297 | 0.0000825422 |
39049000220 | 0.228277 | 0.0001035583 |
39049000310 | 0.014617 | 0.0000954292 |
39049000320 | 0.095630 | 0.0000632660 |
39049000330 | 0.022402 | 0.0000627222 |
39049000410 | 0.229007 | 0.0000667460 |
39049000420 | 0.223597 | 0.0000913782 |
39049000500 | 0.164556 | 0.0001101106 |
39049000600 | 0.050748 | 0.0000954020 |
39049000710 | 0.096691 | 0.0000889313 |
39049000720 | 0.506840 | 0.0000655770 |
39049000730 | 1.226413 | 0.0000948038 |
39049000810 | 0.163030 | 0.0000713680 |
39049000820 | 0.302157 | 0.0000831675 |
39049000910 | 0.741400 | 0.0000921938 |
39049000920 | 0.710846 | 0.0000554087 |
39049001000 | 0.128963 | 0.0001617130 |
39049001110 | 0.321770 | 0.0000742227 |
39049001121 | 0.103252 | 0.0002703826 |
39049001122 | 0.320905 | 0.0000830587 |
39049001200 | 0.070144 | 0.0001085337 |
39049001300 | 0.097875 | 0.0001538557 |
39049001400 | 0.886682 | 0.0000430383 |
39049001500 | 1.129541 | 0.0000499712 |
39049001600 | 0.130765 | 0.0000488021 |
39049001700 | 0.009173 | 0.0000863213 |
39049001810 | 0.108104 | 0.0001061412 |
39049001820 | 0.106847 | 0.0000665285 |
39049001901 | 0.094054 | 0.0000743314 |
39049001902 | 0.152466 | 0.0001104640 |
39049002000 | 0.093391 | 0.0000904538 |
39049002100 | 0.129266 | 0.0000649788 |
39049002200 | 0.035349 | 0.0000615260 |
39049002300 | 0.941394 | 0.0000353441 |
39049002510 | 1.100917 | 0.0000746849 |
39049002520 | 0.741898 | 0.0000805031 |
39049002600 | 0.608222 | 0.0000978217 |
39049002710 | 0.933876 | 0.0000546475 |
39049002730 | 0.744325 | 0.0000606016 |
39049002740 | 0.097046 | 0.0000715855 |
39049002750 | 0.592163 | 0.0000604928 |
39049002760 | 0.136095 | 0.0000949398 |
39049002770 | 0.555529 | 0.0000610910 |
39049002780 | 0.145267 | 0.0000579644 |
39049002800 | 0.793123 | 0.0000542668 |
39049002900 | 1.338850 | 0.0000739780 |
39049003000 | 0.021631 | 0.0001057877 |
39049003200 | 0.129225 | 0.0000811828 |
39049003600 | 0.444543 | 0.0000336313 |
39049003700 | 0.305747 | 0.0000836297 |
39049003800 | 0.152539 | 0.0000577741 |
39049004000 | 0.045899 | 0.0000883060 |
39049004200 | 0.302901 | 0.0000116364 |
39049004300 | 0.072615 | 0.0001457810 |
39049004500 | 0.065497 | 0.0001357215 |
39049004610 | 0.156743 | 0.0000982567 |
39049004620 | 0.113079 | 0.0000744130 |
39049004700 | 0.145423 | 0.0001532304 |
39049004810 | 0.060503 | 0.0000734614 |
39049004820 | 0.019915 | 0.0000688939 |
39049004900 | 0.008213 | 0.0001324318 |
39049005000 | 0.074008 | 0.0001267767 |
39049005100 | 0.511627 | 0.0000595685 |
39049005200 | 0.171751 | 0.0000790621 |
39049005300 | 0.435779 | 0.0000753374 |
39049005410 | 0.984237 | 0.0000402108 |
39049005420 | 1.167251 | 0.0000498080 |
39049005500 | 1.052601 | 0.0001104368 |
39049005610 | 0.655235 | 0.0000452133 |
39049005620 | 0.215642 | 0.0000584538 |
39049005700 | 0.194369 | 0.0000962720 |
39049005810 | 0.161018 | 0.0000785999 |
39049005820 | 0.158053 | 0.0000603569 |
39049005900 | 0.854140 | 0.0000677792 |
39049006000 | 0.120229 | 0.0000578013 |
39049006100 | 0.015264 | 0.0000606560 |
39049006220 | 0.196866 | 0.0002199765 |
39049006230 | 0.351108 | 0.0005084662 |
39049006236 | 0.251291 | 0.0001622568 |
39049006310 | 0.253723 | 0.0001162822 |
39049006321 | 0.221954 | 0.0001154394 |
39049006323 | 0.252666 | 0.0000917044 |
39049006330 | 0.260049 | 0.0001331386 |
39049006340 | 0.265097 | 0.0000914054 |
39049006351 | 0.022517 | 0.0001128837 |
39049006352 | 0.244461 | 0.0000852066 |
39049006353 | 0.069153 | 0.0001352049 |
39049006371 | 0.076727 | 0.0001891183 |
39049006372 | 0.050882 | 0.0001743010 |
39049006383 | 0.121342 | 0.0002509977 |
39049006384 | 0.068890 | 0.0001590214 |
39049006386 | 0.244814 | 0.0001166085 |
39049006387 | 0.030762 | 0.0001646493 |
39049006391 | 0.233929 | 0.0001473035 |
39049006392 | 0.253123 | 0.0001233238 |
39049006393 | 0.175065 | 0.0001456178 |
39049006394 | 0.196494 | 0.0000735158 |
39049006395 | 0.105165 | 0.0000924657 |
39049006396 | 0.201452 | 0.0001418931 |
39049006410 | 0.240767 | 0.0000741683 |
39049006430 | 0.215721 | 0.0001353409 |
39049006500 | 0.259130 | 0.0000937707 |
39049006600 | 0.254674 | 0.0001060596 |
39049006710 | 0.134480 | 0.0000719933 |
39049006721 | 0.259100 | 0.0001007580 |
39049006722 | 0.209159 | 0.0000795515 |
39049006810 | 0.231067 | 0.0000622872 |
39049006821 | 0.106944 | 0.0000849075 |
39049006822 | 0.173625 | 0.0000515209 |
39049006910 | 0.223463 | 0.0000438811 |
39049006921 | 0.043813 | 0.0001024164 |
39049006923 | 0.070279 | 0.0000972779 |
39049006924 | 0.284015 | 0.0001073102 |
39049006931 | 0.499257 | 0.0001887377 |
39049006932 | 0.465750 | 0.0001853120 |
39049006933 | 0.727239 | 0.0001867530 |
39049006942 | 0.438793 | 0.0000372745 |
39049006943 | 0.189689 | 0.0001270758 |
39049006944 | 0.092550 | 0.0001118234 |
39049006945 | 0.520543 | 0.0001539373 |
39049006950 | 0.238226 | 0.0000671267 |
39049006990 | 0.015864 | 0.0002043707 |
39049007010 | 0.051961 | 0.0001153850 |
39049007020 | 0.186664 | 0.0001863180 |
39049007041 | 0.266166 | 0.0000678336 |
39049007043 | 0.035355 | 0.0001422194 |
39049007044 | 0.194423 | 0.0001636433 |
39049007047 | 0.009101 | 0.0001006764 |
39049007048 | 0.066585 | 0.0001741922 |
39049007112 | 0.266424 | 0.0001653018 |
39049007113 | 0.290460 | 0.0001525507 |
39049007114 | 0.108015 | 0.0001272661 |
39049007115 | 0.404778 | 0.0001655465 |
39049007120 | 0.117094 | 0.0001240579 |
39049007132 | 0.067330 | 0.0002207377 |
39049007193 | 0.246752 | 0.0001811523 |
39049007194 | 0.064214 | 0.0001756060 |
39049007198 | 0.048238 | 0.0000734614 |
39049007199 | 0.100701 | 0.0001727513 |
39049007201 | 0.139637 | 0.0000177808 |
39049007202 | 0.256365 | 0.0000992626 |
39049007203 | 0.147183 | 0.0001249823 |
39049007205 | 0.121568 | 0.0001569823 |
39049007207 | 0.033492 | 0.0002086663 |
39049007209 | 0.047240 | 0.0002306885 |
39049007210 | 0.072614 | 0.0002586647 |
39049007393 | 0.097090 | 0.0002411014 |
39049007394 | 0.169315 | 0.0000787087 |
39049007395 | 0.072862 | 0.0003689656 |
39049007396 | 0.069594 | 0.0003175807 |
39049007424 | 0.026766 | 0.0001583417 |
39049007425 | 0.114037 | 0.0000737877 |
39049007426 | 0.182144 | 0.0000886866 |
39049007427 | 0.040093 | 0.0001789501 |
39049007492 | 0.119003 | 0.0001555686 |
39049007494 | 0.045474 | 0.0001222091 |
39049007511 | 1.016537 | 0.0000485030 |
39049007512 | 1.117581 | 0.0001068752 |
39049007520 | 0.904531 | 0.0000545115 |
39049007531 | 0.568540 | 0.0000871097 |
39049007532 | 1.035872 | 0.0000690570 |
39049007533 | 0.789312 | 0.0000529618 |
39049007534 | 0.864480 | 0.0000963807 |
39049007550 | 0.639872 | 0.0000827325 |
39049007551 | 0.997396 | 0.0002731286 |
39049007710 | 0.122694 | 0.0001162822 |
39049007721 | 0.832658 | 0.0001917827 |
39049007722 | 0.092248 | 0.0001050808 |
39049007730 | 0.070193 | 0.0000795515 |
39049007740 | 0.125597 | 0.0000433373 |
39049007811 | 0.094076 | 0.0001045099 |
39049007812 | 0.146419 | 0.0001257436 |
39049007820 | 0.776517 | 0.0000911335 |
39049007830 | 0.094518 | 0.0000879797 |
39049007921 | 0.113665 | 0.0002795449 |
39049007922 | 0.182884 | 0.0001586136 |
39049007931 | 0.143845 | 0.0001259882 |
39049007933 | 0.189408 | 0.0002026850 |
39049007941 | 0.057820 | 0.0000815906 |
39049007951 | 0.124373 | 0.0002511065 |
39049007952 | 0.254055 | 0.0002195686 |
39049007953 | 0.008807 | 0.0001961600 |
39049007954 | 0.011929 | 0.0002157080 |
39049008000 | 0.219132 | 0.0001440409 |
39049008110 | 0.015491 | 0.0001180222 |
39049008120 | 0.062952 | 0.0001078540 |
39049008132 | 0.047270 | 0.0001864267 |
39049008141 | 0.141616 | 0.0002029297 |
39049008142 | 0.015237 | 0.0002026306 |
39049008161 | 0.008201 | 0.0002140223 |
39049008162 | 0.064101 | 0.0002407208 |
39049008163 | 0.119284 | 0.0000949126 |
39049008164 | 0.029581 | 0.0001182125 |
39049008210 | 0.121179 | 0.0000587800 |
39049008230 | 0.680842 | 0.0000596772 |
39049008241 | 0.047673 | 0.0000626951 |
39049008242 | 0.030729 | 0.0001445031 |
39049008311 | 0.041113 | 0.0001187835 |
39049008312 | 0.036244 | 0.0001190554 |
39049008321 | 0.105224 | 0.0000642720 |
39049008322 | 0.008771 | 0.0001171522 |
39049008330 | 0.267272 | 0.0000370570 |
39049008340 | 0.078392 | 0.0001647852 |
39049008350 | 0.101084 | 0.0001848770 |
39049008360 | 0.001982 | 0.0001791948 |
39049008370 | 0.134909 | 0.0002181005 |
39049008380 | 0.042804 | 0.0001540189 |
39049008400 | 0.201693 | 0.0000869194 |
39049008500 | 0.218058 | 0.0001446119 |
39049008710 | 1.071200 | 0.0000658760 |
39049008720 | 0.292441 | 0.0000799321 |
39049008730 | 0.592244 | 0.0000478777 |
39049008811 | 0.097794 | 0.0000457027 |
39049008812 | 0.567213 | 0.0000785455 |
39049008813 | 0.960454 | 0.0000594869 |
39049008821 | 0.164492 | 0.0000693833 |
39049008822 | 0.073677 | 0.0001113884 |
39049008825 | 0.123135 | 0.0001823486 |
39049008900 | 0.058566 | 0.0001423009 |
39049009000 | 0.166299 | 0.0000930910 |
39049009100 | 0.156583 | 0.0001278642 |
39049009210 | 0.546425 | 0.0001390112 |
39049009220 | 0.141859 | 0.0000587800 |
39049009230 | 0.197931 | 0.0001143519 |
39049009240 | 0.083432 | 0.0000495905 |
39049009250 | 0.281909 | 0.0000452405 |
39049009311 | 0.571259 | 0.0000828412 |
39049009312 | 0.587798 | 0.0000858591 |
39049009321 | 0.353898 | 0.0000595141 |
39049009322 | 0.322763 | 0.0000906713 |
39049009323 | 1.055383 | 0.0001110621 |
39049009325 | 0.721345 | 0.0001219645 |
39049009326 | 0.902245 | 0.0000475515 |
39049009331 | 1.161892 | 0.0000308038 |
39049009332 | 1.061288 | 0.0000959457 |
39049009333 | 0.916716 | 0.0000589160 |
39049009334 | 1.025253 | 0.0000809109 |
39049009336 | 0.404144 | 0.0000562787 |
39049009337 | 1.200762 | 0.0001123672 |
39049009340 | 0.446852 | 0.0000846900 |
39049009350 | 0.440473 | 0.0000760715 |
39049009361 | 0.358912 | 0.0001375159 |
39049009362 | 0.022362 | 0.0001744913 |
39049009371 | 0.842842 | 0.0001724794 |
39049009372 | 0.547664 | 0.0001188922 |
39049009373 | 0.688269 | 0.0001630180 |
39049009374 | 0.456193 | 0.0002418898 |
39049009381 | 0.036786 | 0.0001514360 |
39049009382 | 0.192419 | 0.0000799593 |
39049009383 | 0.090041 | 0.0000714223 |
39049009384 | 0.015794 | 0.0000625591 |
39049009385 | 0.123583 | 0.0000944776 |
39049009386 | 0.414767 | 0.0000659848 |
39049009390 | 0.067784 | 0.0001547801 |
39049009410 | 0.155683 | 0.0000908072 |
39049009420 | 0.204683 | 0.0001623655 |
39049009430 | 0.124866 | 0.0002416451 |
39049009440 | 0.021822 | 0.0001207138 |
39049009450 | 0.066886 | 0.0002780496 |
39049009495 | 0.102911 | 0.0001323230 |
39049009497 | 0.218920 | 0.0000469261 |
39049009520 | 0.064366 | 0.0001255261 |
39049009590 | 0.174398 | 0.0001406697 |
39049009600 | 0.037214 | 0.0001203060 |
39049009711 | 0.177181 | 0.0001255261 |
39049009712 | 0.219377 | 0.0000780562 |
39049009720 | 0.229359 | 0.0001816417 |
39049009740 | 0.153705 | 0.0004512087 |
39049009751 | 0.265231 | 0.0001567648 |
39049009752 | 0.100077 | 0.0001848498 |
39049009800 | 0.339872 | 0.0001901786 |
39049009900 | 0.495715 | 0.0000466271 |
39049010000 | 0.085199 | 0.0001457538 |
39049010100 | 0.430568 | 0.0000312660 |
39049010200 | 0.238238 | 0.0004549062 |
39049010300 | 0.053665 | 0.0000585897 |
39049010400 | 0.278738 | 0.0001954259 |
39049010500 | 0.436621 | 0.0002380292 |
39049010601 | 0.145332 | 0.0001416756 |
39049010602 | 0.037932 | 0.0001804182 |
39049010700 | 0.084366 | 0.0000352082 |
39051040100 | 0.287414 | 0.0000811284 |
39051040200 | 0.244327 | 0.0001221548 |
39051040300 | 0.272231 | 0.0001259067 |
39055310600 | 0.271933 | 0.0001802007 |
39055310700 | 0.278877 | 0.0000994801 |
39055311400 | 0.264596 | 0.0001475210 |
39055311500 | 0.283466 | 0.0001459441 |
39055311600 | 0.347559 | 0.0001026611 |
39055311700 | 0.130016 | 0.0001175328 |
39055311800 | 0.272197 | 0.0001920274 |
39055311900 | 0.317516 | 0.0001755516 |
39055312202 | 0.270026 | 0.0001170978 |
39057200101 | 0.133720 | 0.0000747664 |
39057200103 | 0.025051 | 0.0000922754 |
39057200104 | 0.017416 | 0.0001505116 |
39057200300 | 0.141202 | 0.0000981479 |
39057200400 | 0.179110 | 0.0000531793 |
39057200500 | 0.119540 | 0.0001307733 |
39057200600 | 0.128680 | 0.0000981479 |
39057200700 | 0.044744 | 0.0001072559 |
39057200900 | 0.133087 | 0.0001681293 |
39057210100 | 0.126513 | 0.0001321327 |
39057210200 | 0.236267 | 0.0002166052 |
39057210300 | 0.283368 | 0.0000931454 |
39057210401 | 0.141005 | 0.0001292780 |
39057210402 | 0.156068 | 0.0001346340 |
39057210500 | 0.189613 | 0.0001489347 |
39057210601 | 0.185551 | 0.0002379476 |
39057210602 | 0.235463 | 0.0001352593 |
39057210603 | 0.125335 | 0.0001899883 |
39057220100 | 0.222538 | 0.0002119289 |
39057220200 | 0.155835 | 0.0002168499 |
39057240100 | 0.181520 | 0.0000804759 |
39057240200 | 0.165750 | 0.0001312899 |
39057240301 | 0.149507 | 0.0002253325 |
39057240302 | 0.097439 | 0.0001026067 |
39057240500 | 0.144829 | 0.0001197079 |
39057240600 | 0.289908 | 0.0001264504 |
39057240700 | 0.176812 | 0.0000724555 |
39057280300 | 0.008488 | 0.0000618794 |
39061000200 | 1.426815 | 0.0000230281 |
39061000700 | 0.088424 | 0.0000515481 |
39061000900 | 0.153607 | 0.0000498896 |
39061001000 | 0.065357 | 0.0000399661 |
39061001100 | 0.253609 | 0.0000290366 |
39061001600 | 0.887227 | 0.0000211793 |
39061001700 | 0.841029 | 0.0000253934 |
39061001800 | 0.155158 | 0.0000404283 |
39061001900 | 0.142422 | 0.0000497265 |
39061002000 | 0.084737 | 0.0000392048 |
39061002200 | 0.759184 | 0.0000557622 |
39061002300 | 0.696058 | 0.0000260731 |
39061002500 | 0.140872 | 0.0000717214 |
39061002600 | 0.039854 | 0.0000893663 |
39061002700 | 0.090616 | 0.0000420323 |
39061002800 | 0.118595 | 0.0000363773 |
39061002900 | 0.131623 | 0.0001175600 |
39061003000 | 0.060546 | 0.0001283536 |
39061003200 | 0.235546 | 0.0000426305 |
39061003300 | 0.120326 | 0.0000596228 |
39061003600 | 1.329990 | 0.0000322447 |
39061003700 | 0.882301 | 0.0000386339 |
39061003800 | 1.429081 | 0.0000537775 |
39061003900 | 0.990279 | 0.0000458658 |
39061004000 | 0.453158 | 0.0000544572 |
39061004100 | 0.277052 | 0.0000421955 |
39061004200 | 0.044472 | 0.0000478505 |
39061004500 | 0.242952 | 0.0000262090 |
39061004602 | 0.020920 | 0.0001202788 |
39061004603 | 0.170864 | 0.0000791165 |
39061004604 | 0.056403 | 0.0001041293 |
39061004605 | 0.067870 | 0.0000669364 |
39061004701 | 0.226626 | 0.0000835481 |
39061004702 | 0.293605 | 0.0000174546 |
39061004800 | 0.205100 | 0.0000929279 |
39061004900 | 0.133620 | 0.0001662262 |
39061005000 | 0.115864 | 0.0001262329 |
39061005100 | 0.184804 | 0.0000648701 |
39061005200 | 0.098498 | 0.0000967886 |
39061005301 | 0.072605 | 0.0001136994 |
39061005302 | 0.094520 | 0.0000849619 |
39061005400 | 0.056009 | 0.0000267256 |
39061005500 | 0.328873 | 0.0000944776 |
39061005600 | 0.114208 | 0.0001644862 |
39061005701 | 0.089255 | 0.0000790349 |
39061005702 | 0.078353 | 0.0001108446 |
39061005800 | 0.561529 | 0.0001333833 |
39061005900 | 0.210768 | 0.0000340391 |
39061006000 | 0.207291 | 0.0001442584 |
39061006100 | 0.216445 | 0.0000788446 |
39061006300 | 1.408521 | 0.0000958642 |
39061006400 | 1.541891 | 0.0000953748 |
39061006500 | 0.340116 | 0.0001563026 |
39061006600 | 1.043285 | 0.0000689754 |
39061006800 | 0.860331 | 0.0001062499 |
39061006900 | 1.315483 | 0.0000755277 |
39061007000 | 0.042097 | 0.0000644079 |
39061007100 | 0.050699 | 0.0000948582 |
39061007200 | 0.098540 | 0.0000641360 |
39061007300 | 0.375185 | 0.0000553000 |
39061007400 | 0.013692 | 0.0000441802 |
39061007500 | 0.133421 | 0.0000543756 |
39061007700 | 1.425691 | 0.0000774580 |
39061007800 | 0.097434 | 0.0000691658 |
39061007900 | 0.234121 | 0.0000404826 |
39061008000 | 1.215726 | 0.0001561395 |
39061008100 | 0.968255 | 0.0000758268 |
39061008201 | 0.701353 | 0.0001014649 |
39061008202 | 0.601232 | 0.0000961360 |
39061008300 | 0.461408 | 0.0001270486 |
39061008400 | 0.580606 | 0.0000552184 |
39061008501 | 0.612721 | 0.0000752286 |
39061008502 | 1.388678 | 0.0000595141 |
39061008601 | 1.044069 | 0.0000545387 |
39061008800 | 1.168316 | 0.0000792524 |
39061009200 | 0.356134 | 0.0001045915 |
39061009300 | 0.150361 | 0.0000573119 |
39061009400 | 0.493555 | 0.0000364588 |
39061009500 | 0.195350 | 0.0000583450 |
39061009600 | 0.064014 | 0.0000895022 |
39061009700 | 0.188366 | 0.0001383587 |
39061009800 | 0.284348 | 0.0000605472 |
39061009901 | 0.111817 | 0.0001070927 |
39061009902 | 0.055617 | 0.0001013289 |
39061010002 | 0.906204 | 0.0001696790 |
39061010003 | 0.646811 | 0.0001397725 |
39061010004 | 1.077677 | 0.0001249551 |
39061010005 | 0.287930 | 0.0000431470 |
39061010100 | 0.372431 | 0.0001158200 |
39061010201 | 0.088062 | 0.0001410775 |
39061010202 | 0.289672 | 0.0000641360 |
39061010300 | 0.121612 | 0.0000347732 |
39061010400 | 0.199423 | 0.0000250671 |
39061010500 | 0.166108 | 0.0000403739 |
39061010600 | 0.176793 | 0.0000392320 |
39061010700 | 0.049324 | 0.0000421683 |
39061010800 | 0.233308 | 0.0000204180 |
39061010900 | 0.357694 | 0.0000699542 |
39061011000 | 1.294099 | 0.0000843637 |
39061011100 | 0.378815 | 0.0000999967 |
39061020401 | 0.253271 | 0.0001318608 |
39061020403 | 0.322915 | 0.0001517623 |
39061020404 | 0.290294 | 0.0001387121 |
39061020501 | 0.223191 | 0.0000736246 |
39061020502 | 0.231448 | 0.0001275380 |
39061020504 | 0.119203 | 0.0000911335 |
39061020505 | 0.115048 | 0.0001178591 |
39061020601 | 0.208489 | 0.0001691625 |
39061020602 | 0.181493 | 0.0002029297 |
39061020701 | 0.132956 | 0.0001722619 |
39061020705 | 0.184850 | 0.0000835481 |
39061020707 | 0.291959 | 0.0001364556 |
39061020741 | 0.242877 | 0.0000790349 |
39061020742 | 0.101037 | 0.0001068480 |
39061020761 | 0.161224 | 0.0001834904 |
39061020762 | 0.031688 | 0.0000873816 |
39061020802 | 0.218027 | 0.0001319696 |
39061020811 | 0.070163 | 0.0001715550 |
39061020812 | 0.180090 | 0.0001235957 |
39061020901 | 0.070741 | 0.0000859678 |
39061020902 | 0.107978 | 0.0001348515 |
39061021001 | 0.233407 | 0.0000849075 |
39061021002 | 0.292822 | 0.0000981751 |
39061021003 | 0.374206 | 0.0000753102 |
39061021101 | 0.235323 | 0.0001353137 |
39061021102 | 0.260140 | 0.0001715550 |
39061021201 | 0.285437 | 0.0000557894 |
39061021202 | 0.158533 | 0.0001375159 |
39061021302 | 0.219188 | 0.0001614683 |
39061021303 | 0.286645 | 0.0001286255 |
39061021304 | 0.266574 | 0.0001346340 |
39061021401 | 0.217922 | 0.0001315074 |
39061021421 | 0.338475 | 0.0001192457 |
39061021422 | 0.089939 | 0.0000802312 |
39061021501 | 0.263679 | 0.0001226713 |
39061021504 | 0.600491 | 0.0001303927 |
39061021505 | 0.573579 | 0.0000842006 |
39061021506 | 0.626530 | 0.0000805303 |
39061021508 | 0.136995 | 0.0001542907 |
39061021509 | 0.245446 | 0.0001756060 |
39061021571 | 0.258199 | 0.0000757452 |
39061021572 | 0.691132 | 0.0001316161 |
39061021602 | 1.029148 | 0.0000816178 |
39061021603 | 0.434082 | 0.0000996976 |
39061021604 | 0.622737 | 0.0001027699 |
39061021701 | 0.206823 | 0.0000699270 |
39061021702 | 0.253317 | 0.0001161463 |
39061021801 | 0.571252 | 0.0001529585 |
39061021802 | 0.536667 | 0.0000800952 |
39061021900 | 0.783395 | 0.0000440986 |
39061022000 | 0.064409 | 0.0000973051 |
39061022101 | 0.142491 | 0.0001167172 |
39061022102 | 0.198914 | 0.0001753341 |
39061022200 | 0.114602 | 0.0001184300 |
39061022301 | 0.184051 | 0.0001750078 |
39061022302 | 0.065991 | 0.0001549976 |
39061022400 | 0.080445 | 0.0000559797 |
39061022500 | 0.484627 | 0.0000943688 |
39061022601 | 0.112810 | 0.0001699781 |
39061022602 | 0.106734 | 0.0000666373 |
39061022700 | 1.330615 | 0.0000878166 |
39061023001 | 0.067892 | 0.0001172882 |
39061023002 | 0.160499 | 0.0001343349 |
39061023100 | 0.150489 | 0.0000719933 |
39061023201 | 0.167909 | 0.0000697911 |
39061023210 | 0.056545 | 0.0001461344 |
39061023222 | 0.106666 | 0.0000682414 |
39061023300 | 0.042836 | 0.0001086152 |
39061023400 | 0.549328 | 0.0000917316 |
39061023501 | 0.227180 | 0.0001149772 |
39061023521 | 0.038432 | 0.0000732983 |
39061023522 | 0.059020 | 0.0001483366 |
39061023600 | 0.162100 | 0.0001066577 |
39061023701 | 0.145327 | 0.0000770774 |
39061023702 | 0.131994 | 0.0000704164 |
39061023800 | 0.297916 | 0.0001255261 |
39061023901 | 0.131644 | 0.0001268039 |
39061023902 | 0.159455 | 0.0001322686 |
39061024001 | 0.077849 | 0.0001384674 |
39061024002 | 0.143463 | 0.0000798777 |
39061024100 | 0.211532 | 0.0001884114 |
39061024200 | 0.049642 | 0.0000701173 |
39061024301 | 0.264844 | 0.0000968973 |
39061024303 | 0.159961 | 0.0001938490 |
39061024321 | 0.120580 | 0.0002220971 |
39061024322 | 0.215127 | 0.0002118745 |
39061024400 | 0.173773 | 0.0001882483 |
39061024700 | 0.187587 | 0.0000471436 |
39061024800 | 0.239755 | 0.0000946951 |
39061024901 | 0.342826 | 0.0000254750 |
39061024902 | 0.170999 | 0.0002126901 |
39061025001 | 0.243720 | 0.0001715550 |
39061025002 | 0.228202 | 0.0001955890 |
39061025101 | 0.185753 | 0.0001287342 |
39061025102 | 0.095919 | 0.0002017335 |
39061025103 | 0.211944 | 0.0001856927 |
39061025104 | 0.247335 | 0.0000491827 |
39061025200 | 0.016290 | 0.0001178047 |
39061025300 | 0.078317 | 0.0000685948 |
39061025401 | 0.129124 | 0.0000451046 |
39061025402 | 0.160323 | 0.0000861038 |
39061025500 | 0.092221 | 0.0001126390 |
39061025600 | 0.088184 | 0.0000977129 |
39061025700 | 0.047340 | 0.0000539406 |
39061025800 | 0.116863 | 0.0001146509 |
39061026002 | 0.316911 | 0.0001395278 |
39061026102 | 0.287800 | 0.0000799865 |
39061026200 | 0.285181 | 0.0000355073 |
39061026300 | 0.262852 | 0.0000237893 |
39061026400 | 1.020277 | 0.0000739508 |
39061026500 | 0.170676 | 0.0000707970 |
39061026600 | 0.161521 | 0.0000405370 |
39061026700 | 1.261440 | 0.0000420867 |
39061026800 | 0.253473 | 0.0000432014 |
39061026900 | 0.762331 | 0.0000624776 |
39061027000 | 1.289044 | 0.0000792252 |
39061027100 | 1.112133 | 0.0001179950 |
39061027200 | 0.509239 | 0.0000505421 |
39061027300 | 0.221623 | 0.0000716127 |
39061027400 | 0.115159 | 0.0001126934 |
39085200100 | 0.115171 | 0.0000491283 |
39085200200 | 0.152322 | 0.0000649788 |
39085200300 | 0.313786 | 0.0000857775 |
39085200400 | 0.226321 | 0.0000954564 |
39085200500 | 0.246815 | 0.0000824606 |
39085200600 | 0.204533 | 0.0000916501 |
39085200700 | 0.118378 | 0.0000989636 |
39085200800 | 0.164998 | 0.0000905354 |
39085200900 | 0.185082 | 0.0000533968 |
39085201000 | 0.066267 | 0.0001290333 |
39085201100 | 0.065415 | 0.0001269398 |
39085201200 | 0.128603 | 0.0000939610 |
39085201300 | 0.223686 | 0.0000953748 |
39085201400 | 0.354369 | 0.0000968429 |
39085201500 | 0.186442 | 0.0000689211 |
39085201600 | 0.168920 | 0.0000957010 |
39085201700 | 0.189940 | 0.0001597283 |
39085201800 | 0.222324 | 0.0001030146 |
39085201900 | 0.109387 | 0.0000755277 |
39085202000 | 0.263456 | 0.0001448294 |
39085202100 | 0.145678 | 0.0000568225 |
39085202400 | 0.267822 | 0.0000827325 |
39085202500 | 0.167261 | 0.0001138081 |
39085202600 | 0.306774 | 0.0000987461 |
39085202700 | 0.235225 | 0.0001735941 |
39085202800 | 0.254227 | 0.0001548889 |
39085202900 | 0.296523 | 0.0001852305 |
39085203000 | 0.335794 | 0.0001756060 |
39085203200 | 0.233175 | 0.0000882788 |
39085203400 | 0.208909 | 0.0001130197 |
39085203500 | 0.219161 | 0.0001803638 |
39085203700 | 0.245593 | 0.0000881428 |
39085204000 | 0.277166 | 0.0000816721 |
39085204200 | 0.331133 | 0.0001067665 |
39085204301 | 0.013401 | 0.0000657945 |
39085204302 | 0.022798 | 0.0001453731 |
39085204400 | 0.333590 | 0.0000919491 |
39085204500 | 0.305190 | 0.0001059237 |
39085204700 | 0.176543 | 0.0001215023 |
39085204800 | 0.350335 | 0.0001442313 |
39085204900 | 0.221086 | 0.0001551064 |
39085205001 | 0.246354 | 0.0001446663 |
39085205002 | 0.292044 | 0.0001546714 |
39085205100 | 0.272745 | 0.0001854751 |
39085205300 | 0.285472 | 0.0000629397 |
39085205400 | 0.278527 | 0.0000431742 |
39085205701 | 0.263726 | 0.0001296042 |
39085205702 | 0.216546 | 0.0000886866 |
39085205800 | 0.294343 | 0.0000344469 |
39085205900 | 0.270169 | 0.0000282481 |
39085206000 | 0.186971 | 0.0001397996 |
39085206100 | 0.241690 | 0.0000852881 |
39085206200 | 0.212053 | 0.0000381717 |
39085206300 | 0.173085 | 0.0001313171 |
39085206400 | 0.280447 | 0.0001236773 |
39085206500 | 0.179427 | 0.0000930095 |
39085206600 | 0.146549 | 0.0001281361 |
39087050100 | 0.265139 | 0.0000811556 |
39087050200 | 0.311867 | 0.0000534240 |
39087050300 | 0.106048 | 0.0000587800 |
39087050400 | 0.274732 | 0.0000823246 |
39087050700 | 0.343473 | 0.0001005948 |
39087050800 | 0.317147 | 0.0001005948 |
39087050900 | 0.279316 | 0.0000527987 |
39087051001 | 0.150568 | 0.0001225354 |
39087051002 | 0.265842 | 0.0001170707 |
39087051100 | 0.249098 | 0.0001734853 |
39087051200 | 0.230351 | 0.0001341174 |
39087051300 | 0.334538 | 0.0001011930 |
39087051401 | 0.290985 | 0.0001398268 |
39087051402 | 0.291621 | 0.0000911607 |
39089755900 | 0.036070 | 0.0001729416 |
39089756201 | 0.059969 | 0.0000648429 |
39089756202 | 0.021559 | 0.0002263656 |
39089756500 | 0.132361 | 0.0001150859 |
39089756800 | 0.194493 | 0.0002260122 |
39089757100 | 0.232829 | 0.0001120409 |
39089757400 | 0.200770 | 0.0001897436 |
39093010200 | 0.282160 | 0.0001072287 |
39093010300 | 0.207198 | 0.0001482007 |
39093010400 | 0.193441 | 0.0001889552 |
39093013100 | 0.259195 | 0.0002531456 |
39093013200 | 0.089489 | 0.0007296661 |
39093021100 | 0.181669 | 0.0001773732 |
39093021200 | 0.193927 | 0.0001511913 |
39093022100 | 0.157864 | 0.0000529075 |
39093022200 | 0.308353 | 0.0000719389 |
39093022400 | 0.168437 | 0.0000989908 |
39093022500 | 0.163610 | 0.0000444249 |
39093022601 | 0.078779 | 0.0000659304 |
39093022800 | 0.418631 | 0.0001108175 |
39093023000 | 0.109016 | 0.0001319696 |
39093023100 | 0.793782 | 0.0000906169 |
39093023200 | 0.364190 | 0.0000790077 |
39093023300 | 0.378757 | 0.0000606560 |
39093023400 | 0.183179 | 0.0000534512 |
39093023500 | 0.101539 | 0.0000521734 |
39093023600 | 0.518583 | 0.0000681870 |
39093023700 | 0.160374 | 0.0001276739 |
39093023800 | 0.319730 | 0.0000399389 |
39093023900 | 0.075417 | 0.0000436908 |
39093024000 | 0.109672 | 0.0000475515 |
39093024100 | 0.093105 | 0.0000874088 |
39093024200 | 0.114812 | 0.0001347155 |
39093028100 | 0.091308 | 0.0002247887 |
39093030100 | 0.218516 | 0.0001781344 |
39093050100 | 0.332856 | 0.0000827868 |
39093050200 | 0.222258 | 0.0000924929 |
39093050300 | 0.164678 | 0.0002164420 |
39093050400 | 0.261787 | 0.0000634835 |
39093057100 | 0.260631 | 0.0001019270 |
39093070101 | 0.114732 | 0.0000927376 |
39093070102 | 0.022180 | 0.0002813393 |
39093070200 | 0.083845 | 0.0000520103 |
39093070300 | 0.144506 | 0.0000815634 |
39093070400 | 0.047299 | 0.0001203332 |
39093070500 | 0.073811 | 0.0000840919 |
39093070600 | 0.085587 | 0.0002560547 |
39093070700 | 0.061378 | 0.0001244657 |
39093070800 | 0.055526 | 0.0000264537 |
39093070901 | 0.282018 | 0.0000495634 |
39093070902 | 0.035068 | 0.0000984742 |
39093071000 | 0.121230 | 0.0000430383 |
39093071100 | 0.081492 | 0.0001146509 |
39093071201 | 0.064750 | 0.0001091318 |
39093071202 | 0.091170 | 0.0002137505 |
39093071300 | 0.172164 | 0.0001171250 |
39093071400 | 0.419203 | 0.0000841190 |
39093071500 | 0.115106 | 0.0000567681 |
39093077100 | 0.272921 | 0.0000965439 |
39093080101 | 0.195540 | 0.0000578556 |
39093080103 | 0.195224 | 0.0001216110 |
39093080104 | 0.274159 | 0.0000956467 |
39093080500 | 0.145562 | 0.0004002587 |
39093080600 | 0.172532 | 0.0001467054 |
39093080700 | 0.168896 | 0.0005397321 |
39093090100 | 0.289253 | 0.0000999967 |
39093090200 | 0.322526 | 0.0000966254 |
39093091100 | 0.185920 | 0.0001796570 |
39093091200 | 0.104337 | 0.0000991811 |
39093092100 | 0.255912 | 0.0000647070 |
39093095100 | 0.066267 | 0.0002214174 |
39093097200 | 0.047878 | 0.0002273444 |
39093097300 | 0.472605 | 0.0000708242 |
39093097400 | 0.235324 | 0.0002945798 |
39095000200 | 0.046843 | 0.0001292508 |
39095000300 | 0.058137 | 0.0001135634 |
39095000400 | 0.070287 | 0.0001063043 |
39095000600 | 0.102313 | 0.0001099474 |
39095000700 | 0.119821 | 0.0001192457 |
39095000800 | 1.124841 | 0.0000320000 |
39095000900 | 0.527959 | 0.0000476330 |
39095001000 | 0.635926 | 0.0001097299 |
39095001100 | 0.830986 | 0.0000558437 |
39095001201 | 0.025704 | 0.0000602210 |
39095001202 | 0.480569 | 0.0000740596 |
39095001301 | 0.175758 | 0.0000740324 |
39095001302 | 0.101963 | 0.0000482855 |
39095001303 | 0.325047 | 0.0000772405 |
39095001400 | 1.141035 | 0.0000357520 |
39095001500 | 1.078838 | 0.0000303416 |
39095001600 | 0.653572 | 0.0000761530 |
39095001700 | 0.824463 | 0.0000299338 |
39095001800 | 0.419323 | 0.0000688939 |
39095001900 | 0.635614 | 0.0000345013 |
39095002000 | 0.119068 | 0.0000347460 |
39095002100 | 0.172492 | 0.0000741683 |
39095002200 | 1.122176 | 0.0000339304 |
39095002300 | 1.061977 | 0.0000443977 |
39095002401 | 0.377426 | 0.0000953204 |
39095002402 | 1.467836 | 0.0000382260 |
39095002500 | 1.624399 | 0.0000400476 |
39095002600 | 1.561879 | 0.0000242787 |
39095002700 | 0.566128 | 0.0000245506 |
39095002800 | 0.301810 | 0.0000373560 |
39095002900 | 0.570926 | 0.0000521190 |
39095003000 | 0.205861 | 0.0000503246 |
39095003100 | 1.031876 | 0.0000269975 |
39095003200 | 1.624223 | 0.0000292541 |
39095003300 | 1.427711 | 0.0000331963 |
39095003400 | 0.709327 | 0.0000193305 |
39095003500 | 1.372810 | 0.0000254478 |
39095003600 | 1.298490 | 0.0000312388 |
39095003700 | 0.512291 | 0.0000302872 |
39095003900 | 0.147185 | 0.0001436331 |
39095004000 | 0.316272 | 0.0000424130 |
39095004200 | 0.221296 | 0.0000387426 |
39095004400 | 0.040241 | 0.0000970876 |
39095004501 | 0.085914 | 0.0000642991 |
39095004503 | 0.157636 | 0.0000735430 |
39095004504 | 0.203881 | 0.0000973595 |
39095004600 | 0.145819 | 0.0000641088 |
39095004701 | 0.074185 | 0.0000561972 |
39095004702 | 0.068754 | 0.0000843637 |
39095004800 | 0.045797 | 0.0000670179 |
39095004900 | 0.067005 | 0.0000742227 |
39095005000 | 0.065541 | 0.0000449142 |
39095005100 | 0.087102 | 0.0001103009 |
39095005200 | 0.134078 | 0.0000777571 |
39095005300 | 0.206474 | 0.0000551640 |
39095005400 | 0.132042 | 0.0000699542 |
39095005501 | 0.174107 | 0.0000656313 |
39095005502 | 0.229294 | 0.0000823790 |
39095005503 | 0.208891 | 0.0000634019 |
39095005600 | 0.112041 | 0.0001387665 |
39095005701 | 0.004194 | 0.0001016008 |
39095005702 | 0.104548 | 0.0001304470 |
39095005703 | 0.137904 | 0.0000695736 |
39095005801 | 0.054122 | 0.0000898557 |
39095005802 | 0.075495 | 0.0001290061 |
39095005901 | 0.146597 | 0.0000808293 |
39095005902 | 0.111879 | 0.0001142975 |
39095006000 | 0.094755 | 0.0000706611 |
39095006100 | 0.091612 | 0.0000850978 |
39095006200 | 0.077405 | 0.0000700086 |
39095006300 | 0.022319 | 0.0000814818 |
39095006400 | 0.051448 | 0.0000637554 |
39095006500 | 0.149898 | 0.0000620969 |
39095006600 | 0.930850 | 0.0000666917 |
39095006700 | 0.298517 | 0.0000417333 |
39095006800 | 0.057289 | 0.0001467325 |
39095006900 | 0.111552 | 0.0000710689 |
39095007001 | 0.120048 | 0.0001026611 |
39095007002 | 0.235522 | 0.0000528803 |
39095007101 | 0.200248 | 0.0001179950 |
39095007102 | 0.229076 | 0.0000952660 |
39095007202 | 0.009825 | 0.0000957554 |
39095007203 | 0.062367 | 0.0001005948 |
39095007204 | 0.013005 | 0.0001220460 |
39095007205 | 0.108397 | 0.0001391200 |
39095007301 | 0.051953 | 0.0001356943 |
39095007302 | 0.108266 | 0.0000745761 |
39095007303 | 0.278237 | 0.0001311539 |
39095007400 | 0.190978 | 0.0001683196 |
39095007500 | 0.111793 | 0.0001044555 |
39095007600 | 0.184700 | 0.0001161735 |
39095007700 | 0.094584 | 0.0000901547 |
39095007800 | 0.074644 | 0.0000949126 |
39095007901 | 0.216385 | 0.0000566322 |
39095007902 | 0.064047 | 0.0001455363 |
39095008000 | 0.141451 | 0.0000990180 |
39095008100 | 0.110568 | 0.0001061140 |
39095008201 | 0.226922 | 0.0001318608 |
39095008202 | 0.153883 | 0.0001471947 |
39095008203 | 0.136935 | 0.0001993953 |
39095008301 | 0.036590 | 0.0001666068 |
39095008302 | 0.139432 | 0.0000428752 |
39095008400 | 0.037903 | 0.0001123128 |
39095008500 | 0.114272 | 0.0001142703 |
39095008600 | 0.099825 | 0.0001403978 |
39095008700 | 0.014406 | 0.0001835448 |
39095008800 | 0.083387 | 0.0002010538 |
39095008901 | 0.277767 | 0.0001594021 |
39095008902 | 0.254458 | 0.0001592933 |
39095009000 | 0.181121 | 0.0003337846 |
39095009101 | 0.024718 | 0.0001213663 |
39095009102 | 0.066652 | 0.0001418659 |
39095009201 | 0.168821 | 0.0002169314 |
39095009202 | 0.095411 | 0.0001835992 |
39095009300 | 0.295001 | 0.0000435820 |
39095009400 | 0.086619 | 0.0000668548 |
39095009500 | 0.188069 | 0.0000802312 |
39095009600 | 0.272274 | 0.0000903994 |
39095009700 | 0.249241 | 0.0000834937 |
39095009800 | 0.214150 | 0.0001125303 |
39095009900 | 0.162802 | 0.0001160647 |
39095010001 | 0.197014 | 0.0001099203 |
39095010002 | 0.076938 | 0.0000927919 |
39095010100 | 0.110952 | 0.0001012745 |
39095010200 | 0.024506 | 0.0000758811 |
39095010300 | 0.254941 | 0.0000440714 |
39095010400 | 0.015546 | 0.0000872456 |
39097040400 | 0.277570 | 0.0000718302 |
39097040500 | 0.316257 | 0.0001255261 |
39099800300 | 0.630524 | 0.0000301241 |
39099800400 | 0.756995 | 0.0000223484 |
39099800500 | 0.611313 | 0.0000760443 |
39099800600 | 0.988226 | 0.0000424673 |
39099801000 | 0.350606 | 0.0000307494 |
39099801100 | 0.243594 | 0.0000570128 |
39099801200 | 0.130641 | 0.0000364316 |
39099801300 | 0.113258 | 0.0000582363 |
39099801400 | 0.072902 | 0.0000654138 |
39099801500 | 0.091041 | 0.0000541581 |
39099801600 | 0.524444 | 0.0000653051 |
39099801700 | 0.574617 | 0.0000284928 |
39099802100 | 1.027828 | 0.0000279219 |
39099802300 | 0.936126 | 0.0000181071 |
39099802400 | 0.829542 | 0.0000638913 |
39099802500 | 0.707038 | 0.0000343654 |
39099802600 | 0.049919 | 0.0000418420 |
39099802701 | 0.090266 | 0.0000914054 |
39099802702 | 0.048192 | 0.0000865931 |
39099802800 | 0.015698 | 0.0000830587 |
39099802900 | 0.120659 | 0.0000708514 |
39099803000 | 0.050891 | 0.0000510315 |
39099804000 | 0.096695 | 0.0000574750 |
39099804100 | 0.432314 | 0.0000317553 |
39099804200 | 0.460897 | 0.0000595685 |
39099804300 | 0.585729 | 0.0000236262 |
39099810100 | 0.064337 | 0.0001064402 |
39099810200 | 0.172540 | 0.0000550825 |
39099810300 | 0.514381 | 0.0000429295 |
39099810600 | 0.142825 | 0.0000752830 |
39099810700 | 0.220042 | 0.0001367002 |
39099810800 | 0.163964 | 0.0000623144 |
39099810900 | 0.131433 | 0.0000568225 |
39099811001 | 0.211851 | 0.0001100290 |
39099811002 | 0.238464 | 0.0001977097 |
39099811100 | 0.229656 | 0.0000319728 |
39099811200 | 0.255082 | 0.0000616347 |
39099811300 | 0.119507 | 0.0001726969 |
39099811400 | 0.065405 | 0.0000727274 |
39099811500 | 0.241008 | 0.0001540461 |
39099811600 | 0.195150 | 0.0000892303 |
39099811700 | 0.081306 | 0.0000678879 |
39099811800 | 0.191803 | 0.0000424402 |
39099811901 | 0.102285 | 0.0001207682 |
39099811902 | 0.237965 | 0.0000797962 |
39099812001 | 0.111938 | 0.0001417028 |
39099812002 | 0.188417 | 0.0001032593 |
39099812100 | 0.176739 | 0.0002433580 |
39099812200 | 0.250853 | 0.0001682381 |
39099812301 | 0.159198 | 0.0001060596 |
39099812302 | 0.092589 | 0.0001603808 |
39099812400 | 0.066482 | 0.0000780018 |
39099812500 | 0.225476 | 0.0001362652 |
39099812601 | 0.003113 | 0.0001120409 |
39099812602 | 0.091604 | 0.0001464878 |
39099812603 | 0.152818 | 0.0002086120 |
39099812700 | 0.263828 | 0.0000534784 |
39099813500 | 0.274951 | 0.0001943112 |
39099813600 | 0.298878 | 0.0002135330 |
39099813700 | 0.452567 | 0.0000842278 |
39099813800 | 0.496591 | 0.0000791709 |
39099813900 | 1.293830 | 0.0000436636 |
39099814000 | 0.539757 | 0.0000887953 |
39099814100 | 0.265198 | 0.0000704164 |
39103400100 | 0.315720 | 0.0002148380 |
39103402000 | 0.298120 | 0.0001442041 |
39103403002 | 0.247759 | 0.0000817537 |
39103404000 | 0.314779 | 0.0001064946 |
39103405000 | 0.287979 | 0.0002474089 |
39103406000 | 0.319797 | 0.0003160309 |
39103407000 | 0.215684 | 0.0001850130 |
39103408001 | 0.320141 | 0.0000755821 |
39103408002 | 0.323377 | 0.0000547290 |
39103408003 | 0.186032 | 0.0000893663 |
39103408100 | 0.112272 | 0.0002013800 |
39103408201 | 0.171576 | 0.0001255261 |
39103408202 | 0.319045 | 0.0001339543 |
39103408301 | 0.206553 | 0.0000839287 |
39103408302 | 0.170535 | 0.0002632322 |
39103409002 | 0.250420 | 0.0001204691 |
39103413000 | 0.297488 | 0.0001651659 |
39103415100 | 0.246186 | 0.0001255804 |
39103415200 | 0.156808 | 0.0001161735 |
39103415300 | 0.285952 | 0.0001090231 |
39103415400 | 0.136312 | 0.0001156025 |
39103415800 | 0.218046 | 0.0001900699 |
39103416000 | 0.258655 | 0.0001464607 |
39103416100 | 0.175398 | 0.0001288430 |
39103416200 | 0.070633 | 0.0001104368 |
39103416300 | 0.215787 | 0.0000722108 |
39103416400 | 0.274329 | 0.0000897469 |
39103417000 | 0.295551 | 0.0002459136 |
39103417100 | 0.265008 | 0.0001770741 |
39103417200 | 0.255272 | 0.0001911030 |
39103417300 | 0.342642 | 0.0001142703 |
39109340100 | 0.346802 | 0.0001415940 |
39109345000 | 0.337715 | 0.0001317521 |
39109350100 | 0.320838 | 0.0002174480 |
39109355001 | 0.256224 | 0.0001545082 |
39109355002 | 0.236552 | 0.0000493187 |
39109365000 | 0.134870 | 0.0002241906 |
39109365101 | 0.245701 | 0.0000946951 |
39109365102 | 0.245622 | 0.0001376246 |
39109365200 | 0.213821 | 0.0001016280 |
39109365301 | 0.154221 | 0.0001647852 |
39109365302 | 0.144207 | 0.0001590486 |
39109380100 | 0.193263 | 0.0002116570 |
39113000100 | 1.553361 | 0.0000649788 |
39113000200 | 1.195635 | 0.0000568769 |
39113000300 | 1.436795 | 0.0000493459 |
39113000400 | 1.427048 | 0.0000986645 |
39113000500 | 1.018677 | 0.0000968701 |
39113000600 | 1.187834 | 0.0000387154 |
39113000700 | 1.517292 | 0.0000575294 |
39113000801 | 0.869274 | 0.0000917044 |
39113000802 | 1.063847 | 0.0000552456 |
39113000900 | 0.589904 | 0.0000703620 |
39113001000 | 1.017309 | 0.0000293356 |
39113001100 | 0.941973 | 0.0000852609 |
39113001200 | 0.351308 | 0.0000256381 |
39113001501 | 0.077078 | 0.0001054343 |
39113001600 | 0.108321 | 0.0000542668 |
39113001700 | 0.121344 | 0.0000190043 |
39113001800 | 0.112954 | 0.0001772916 |
39113001900 | 0.152232 | 0.0001108990 |
39113002000 | 0.054090 | 0.0000732711 |
39113002200 | 0.052093 | 0.0000694376 |
39113002300 | 0.033151 | 0.0000808293 |
39113002400 | 0.198050 | 0.0000667732 |
39113002500 | 0.080516 | 0.0001278098 |
39113002600 | 0.060710 | 0.0001632899 |
39113002700 | 0.140734 | 0.0000528259 |
39113002800 | 0.326877 | 0.0000555719 |
39113002900 | 0.357173 | 0.0001085609 |
39113003000 | 0.156700 | 0.0000729992 |
39113003100 | 0.089083 | 0.0000770502 |
39113003201 | 0.124737 | 0.0001014377 |
39113003300 | 0.026426 | 0.0001375974 |
39113003402 | 0.118342 | 0.0001917827 |
39113003403 | 0.173842 | 0.0000968157 |
39113003404 | 0.039400 | 0.0000551097 |
39113003500 | 1.464386 | 0.0000578013 |
39113003800 | 1.457331 | 0.0000573391 |
39113003900 | 1.599950 | 0.0000499168 |
39113004100 | 1.593058 | 0.0000555175 |
39113004200 | 1.468322 | 0.0000523637 |
39113004300 | 1.490317 | 0.0000524724 |
39113004400 | 1.470674 | 0.0000515753 |
39113004600 | 0.890840 | 0.0000366763 |
39113010100 | 0.272498 | 0.0000563875 |
39113010200 | 0.273963 | 0.0001812610 |
39113020100 | 0.147848 | 0.0000698183 |
39113020200 | 0.219895 | 0.0000771318 |
39113020300 | 0.213468 | 0.0000664742 |
39113020400 | 0.108161 | 0.0001700869 |
39113020500 | 0.127703 | 0.0000362957 |
39113020601 | 0.171550 | 0.0000488837 |
39113020602 | 0.216218 | 0.0000441530 |
39113020700 | 0.182271 | 0.0000841734 |
39113020800 | 0.242118 | 0.0000623416 |
39113020900 | 0.126876 | 0.0000740052 |
39113021000 | 0.171967 | 0.0000470621 |
39113021100 | 0.129820 | 0.0000875175 |
39113021200 | 0.183970 | 0.0000453764 |
39113021301 | 0.265685 | 0.0000704164 |
39113021302 | 0.256407 | 0.0000502702 |
39113021400 | 0.192281 | 0.0000646526 |
39113021501 | 0.043023 | 0.0000720748 |
39113021502 | 0.189806 | 0.0000501887 |
39113021601 | 0.099007 | 0.0000586441 |
39113021602 | 0.153492 | 0.0000871369 |
39113021700 | 0.211263 | 0.0000582363 |
39113021800 | 0.078820 | 0.0000528531 |
39113021900 | 0.178669 | 0.0000591878 |
39113030100 | 0.036891 | 0.0001112525 |
39113030200 | 0.069122 | 0.0000794971 |
39113040101 | 0.172340 | 0.0000461377 |
39113040102 | 0.230847 | 0.0000550553 |
39113040103 | 0.290502 | 0.0000724283 |
39113040201 | 0.258058 | 0.0000730808 |
39113040203 | 0.151548 | 0.0000672898 |
39113040204 | 0.098186 | 0.0001370537 |
39113040302 | 0.120763 | 0.0001312083 |
39113040303 | 0.241751 | 0.0001406968 |
39113040305 | 0.276050 | 0.0000790893 |
39113040306 | 0.100071 | 0.0001275108 |
39113040401 | 0.157348 | 0.0001304199 |
39113040403 | 0.143624 | 0.0001062227 |
39113040405 | 0.082396 | 0.0001384131 |
39113040406 | 0.212037 | 0.0001841973 |
39113050101 | 0.025551 | 0.0001059508 |
39113050103 | 0.135804 | 0.0002242178 |
39113050104 | 0.157368 | 0.0000608735 |
39113050105 | 0.098231 | 0.0001212032 |
39113050301 | 0.185554 | 0.0000729177 |
39113050302 | 0.214414 | 0.0001427903 |
39113050303 | 0.010479 | 0.0000977129 |
39113050401 | 0.179158 | 0.0001339543 |
39113050402 | 0.219668 | 0.0000560340 |
39113050502 | 0.080228 | 0.0000842278 |
39113050503 | 0.301626 | 0.0001663078 |
39113050504 | 0.020520 | 0.0001852576 |
39113050600 | 0.218781 | 0.0001016824 |
39113060100 | 0.139751 | 0.0000826237 |
39113060200 | 0.364732 | 0.0000440986 |
39113060300 | 0.970582 | 0.0001127478 |
39113070101 | 0.485999 | 0.0001205235 |
39113070102 | 0.878762 | 0.0000929551 |
39113070201 | 0.158514 | 0.0000320000 |
39113070202 | 1.395826 | 0.0000483943 |
39113070300 | 0.896338 | 0.0000741139 |
39113070400 | 0.804852 | 0.0000679151 |
39113070500 | 0.997967 | 0.0001016824 |
39113070600 | 0.947601 | 0.0000317282 |
39113070700 | 0.930174 | 0.0000944504 |
39113080100 | 0.857664 | 0.0001557045 |
39113080200 | 0.237440 | 0.0000691658 |
39113080300 | 0.693928 | 0.0000550825 |
39113080400 | 0.489395 | 0.0000771590 |
39113080500 | 0.108183 | 0.0001387665 |
39113080600 | 0.198785 | 0.0000343654 |
39113080700 | 0.272254 | 0.0000596772 |
39113090302 | 0.032467 | 0.0001802007 |
39113090303 | 0.036187 | 0.0000875719 |
39113090304 | 0.043354 | 0.0001802551 |
39113090600 | 0.061037 | 0.0000952932 |
39113090700 | 0.150712 | 0.0000334954 |
39113090800 | 0.307112 | 0.0000368667 |
39113090900 | 0.147654 | 0.0001045099 |
39113091000 | 0.290486 | 0.0000599491 |
39113091100 | 0.021532 | 0.0000798234 |
39113100101 | 0.071705 | 0.0001631812 |
39113100102 | 0.134158 | 0.0001570639 |
39113100201 | 0.079354 | 0.0001165541 |
39113100202 | 0.091309 | 0.0000619338 |
39113100203 | 0.034222 | 0.0001208226 |
39113100301 | 0.102685 | 0.0001031505 |
39113100302 | 0.136755 | 0.0000838472 |
39113100400 | 0.062619 | 0.0001326221 |
39113110100 | 0.289356 | 0.0000387698 |
39113110201 | 0.217136 | 0.0001186475 |
39113110202 | 0.057565 | 0.0000874360 |
39113115002 | 0.275971 | 0.0001077996 |
39113115011 | 0.258671 | 0.0001382499 |
39113115012 | 0.123316 | 0.0001439866 |
39113120101 | 0.059586 | 0.0001327852 |
39113120102 | 0.117785 | 0.0001189194 |
39113120103 | 0.144199 | 0.0000778930 |
39113125000 | 0.226411 | 0.0001686187 |
39113125101 | 0.112079 | 0.0001922721 |
39113125102 | 0.045811 | 0.0001639696 |
39113130101 | 0.293123 | 0.0000632116 |
39113130102 | 0.247645 | 0.0001676671 |
39113140100 | 0.285670 | 0.0001538557 |
39113165100 | 1.367246 | 0.0000633476 |
39113165200 | 0.286777 | 0.0000380901 |
39123051000 | 0.190301 | 0.0001315617 |
39123051100 | 0.226909 | 0.0001018183 |
39129021100 | 0.283673 | 0.0002099442 |
39129021200 | 0.225664 | 0.0002124726 |
39129021402 | 0.252271 | 0.0001746000 |
39133600200 | 0.237243 | 0.0001621208 |
39133600301 | 0.165823 | 0.0002450708 |
39133600302 | 0.229434 | 0.0001850945 |
39133600401 | 0.053524 | 0.0001683468 |
39133600402 | 0.192046 | 0.0002879188 |
39133600403 | 0.100405 | 0.0001274836 |
39133600500 | 0.297655 | 0.0001524420 |
39133600703 | 0.297188 | 0.0000471708 |
39133600704 | 0.333807 | 0.0000488565 |
39133600800 | 0.157598 | 0.0000926288 |
39133600901 | 0.161659 | 0.0001050808 |
39133600902 | 0.195915 | 0.0001322958 |
39133601000 | 0.044209 | 0.0000635923 |
39133601100 | 0.279814 | 0.0001511641 |
39133601200 | 0.091017 | 0.0001299577 |
39133601300 | 0.033467 | 0.0002137505 |
39133601400 | 0.139551 | 0.0001236773 |
39133601501 | 0.207775 | 0.0000523365 |
39133601502 | 0.044260 | 0.0001630724 |
39133601503 | 0.163586 | 0.0000987461 |
39133601600 | 0.249104 | 0.0002236468 |
39133601701 | 0.276928 | 0.0001671778 |
39133601702 | 0.275943 | 0.0001462432 |
39133601801 | 0.195442 | 0.0001015464 |
39133601802 | 0.233317 | 0.0001159831 |
39133602100 | 0.313812 | 0.0001811795 |
39151700100 | 0.174607 | 0.0000280850 |
39151700200 | 0.100815 | 0.0001483638 |
39151700300 | 0.182993 | 0.0000742771 |
39151700400 | 0.123362 | 0.0001279186 |
39151700500 | 0.260001 | 0.0000663110 |
39151700600 | 0.055000 | 0.0000870009 |
39151700700 | 0.059915 | 0.0001777810 |
39151700800 | 0.047693 | 0.0000965982 |
39151701000 | 0.126128 | 0.0000835481 |
39151701100 | 0.040064 | 0.0000872456 |
39151701200 | 0.065049 | 0.0000893119 |
39151701300 | 0.103861 | 0.0000937979 |
39151701500 | 0.235766 | 0.0000561428 |
39151701700 | 0.155434 | 0.0000599763 |
39151701800 | 0.460445 | 0.0000527171 |
39151702100 | 0.745000 | 0.0000811556 |
39151702300 | 0.447373 | 0.0000850434 |
39151702500 | 0.203892 | 0.0000750111 |
39151710900 | 0.263564 | 0.0001180494 |
39151711000 | 0.329479 | 0.0004426173 |
39151711111 | 0.363113 | 0.0001300664 |
39151711112 | 0.236821 | 0.0001368090 |
39151711121 | 0.278781 | 0.0003419137 |
39151711122 | 0.261893 | 0.0001468685 |
39151711202 | 0.268145 | 0.0002266918 |
39151711211 | 0.312030 | 0.0001900971 |
39151711212 | 0.346352 | 0.0000685948 |
39151711311 | 0.132328 | 0.0004514805 |
39151711312 | 0.235573 | 0.0001819135 |
39151711321 | 0.141279 | 0.0001008395 |
39151711322 | 0.095082 | 0.0000897197 |
39151711402 | 0.174334 | 0.0001634802 |
39151711411 | 0.228006 | 0.0001035039 |
39151711412 | 0.258976 | 0.0001134003 |
39151711501 | 0.209069 | 0.0001054887 |
39151711502 | 0.154605 | 0.0000890944 |
39151711600 | 0.172033 | 0.0001653018 |
39151711700 | 0.075102 | 0.0001465150 |
39151711800 | 0.210512 | 0.0001291692 |
39151711900 | 0.176761 | 0.0001366459 |
39151712000 | 0.242982 | 0.0001113612 |
39151712102 | 0.241365 | 0.0002107326 |
39151712111 | 0.252816 | 0.0001622568 |
39151712112 | 0.305293 | 0.0000470893 |
39151712201 | 0.149004 | 0.0001667971 |
39151712202 | 0.104661 | 0.0001509466 |
39151712300 | 0.145100 | 0.0001599186 |
39151712400 | 0.144059 | 0.0001756332 |
39151712500 | 0.299772 | 0.0000531250 |
39151712601 | 0.286077 | 0.0000718302 |
39151712602 | 0.354573 | 0.0001334649 |
39151712700 | 0.294854 | 0.0001373799 |
39151713000 | 0.303275 | 0.0001061140 |
39151713100 | 0.192259 | 0.0001445575 |
39151713201 | 0.201070 | 0.0001881939 |
39151713202 | 0.278869 | 0.0000543212 |
39151713300 | 0.277896 | 0.0001132100 |
39151713401 | 0.219684 | 0.0001325133 |
39151713402 | 0.254923 | 0.0001076365 |
39151713501 | 0.158757 | 0.0001448294 |
39151713502 | 0.188059 | 0.0001620393 |
39151713600 | 0.231436 | 0.0000718030 |
39151713700 | 0.176067 | 0.0000592150 |
39151713900 | 0.202784 | 0.0000503518 |
39151714000 | 0.299541 | 0.0001059237 |
39151714100 | 0.157718 | 0.0000847172 |
39151714200 | 0.177314 | 0.0000598132 |
39151714302 | 0.141260 | 0.0000948310 |
39151714400 | 0.061661 | 0.0001033136 |
39151714600 | 0.288709 | 0.0001138353 |
39151714701 | 0.304865 | 0.0001647309 |
39151714702 | 0.320608 | 0.0000736517 |
39151714801 | 0.309750 | 0.0001742738 |
39151714802 | 0.297969 | 0.0000823246 |
39151714901 | 0.336207 | 0.0001027155 |
39151715000 | 0.244137 | 0.0000757724 |
39153501100 | 0.524073 | 0.0000458114 |
39153501700 | 0.050516 | 0.0000387154 |
39153501800 | 1.600494 | 0.0000225659 |
39153501900 | 1.157614 | 0.0000575294 |
39153502101 | 0.406172 | 0.0000884419 |
39153502102 | 0.179301 | 0.0001152763 |
39153502200 | 0.231764 | 0.0001845236 |
39153502300 | 0.372178 | 0.0001407512 |
39153502500 | 0.207789 | 0.0000271878 |
39153502600 | 0.009326 | 0.0000710145 |
39153502700 | 0.143613 | 0.0001944471 |
39153502800 | 0.117424 | 0.0001104096 |
39153503100 | 0.291589 | 0.0000432830 |
39153503200 | 0.842305 | 0.0000386882 |
39153503300 | 0.062654 | 0.0001300392 |
39153503400 | 0.809741 | 0.0000403195 |
39153503500 | 0.459182 | 0.0000875719 |
39153503600 | 0.101341 | 0.0001142703 |
39153503701 | 0.204739 | 0.0001448838 |
39153503702 | 0.288241 | 0.0001448566 |
39153503800 | 0.232793 | 0.0001038846 |
39153504100 | 0.066437 | 0.0000259643 |
39153504200 | 0.223887 | 0.0000400204 |
39153504400 | 0.281802 | 0.0000323807 |
39153504500 | 0.126010 | 0.0000420867 |
39153504600 | 0.252831 | 0.0000889585 |
39153504700 | 0.147128 | 0.0001268583 |
39153504800 | 0.090916 | 0.0001267767 |
39153505200 | 0.600697 | 0.0000399661 |
39153505300 | 0.683479 | 0.0000367579 |
39153505400 | 0.144279 | 0.0000994801 |
39153505500 | 0.105083 | 0.0000740867 |
39153505600 | 0.295672 | 0.0000255022 |
39153505700 | 0.073748 | 0.0000763433 |
39153505800 | 0.174903 | 0.0001260970 |
39153505900 | 0.124748 | 0.0000581819 |
39153506100 | 0.170711 | 0.0001377606 |
39153506200 | 0.828253 | 0.0000929551 |
39153506400 | 0.174396 | 0.0000750655 |
39153506500 | 1.148115 | 0.0000692473 |
39153506600 | 0.279680 | 0.0000427664 |
39153506700 | 1.288448 | 0.0000429839 |
39153506800 | 0.392437 | 0.0000524724 |
39153507101 | 0.299003 | 0.0001288973 |
39153507102 | 0.048277 | 0.0000856416 |
39153507201 | 0.131311 | 0.0000671539 |
39153507202 | 0.206372 | 0.0000956467 |
39153507203 | 0.063838 | 0.0001298217 |
39153507300 | 0.133762 | 0.0000871369 |
39153507400 | 0.334141 | 0.0000309941 |
39153507500 | 0.256479 | 0.0001691353 |
39153507600 | 0.259196 | 0.0001226442 |
39153508000 | 0.116148 | 0.0001316161 |
39153508301 | 0.107289 | 0.0000662567 |
39153508399 | 0.535963 | 0.0001030689 |
39153508600 | 1.224937 | 0.0000740052 |
39153508800 | 1.085266 | 0.0001460528 |
39153508900 | 0.056964 | 0.0001034496 |
39153509000 | 0.032567 | 0.0000357520 |
39153510100 | 0.230792 | 0.0000688123 |
39153510200 | 0.189575 | 0.0001075549 |
39153510301 | 0.155415 | 0.0001464063 |
39153510302 | 0.274389 | 0.0001576620 |
39153510400 | 0.184097 | 0.0001067937 |
39153510500 | 0.235254 | 0.0001121497 |
39153520103 | 0.067029 | 0.0000600035 |
39153520104 | 0.187417 | 0.0001151947 |
39153520105 | 0.158310 | 0.0001129925 |
39153520106 | 0.149161 | 0.0000668276 |
39153520201 | 0.247404 | 0.0000666645 |
39153520202 | 0.208553 | 0.0001250911 |
39153520301 | 0.223745 | 0.0000874088 |
39153520302 | 0.204842 | 0.0000906169 |
39153520400 | 0.328003 | 0.0001118234 |
39153520500 | 0.213513 | 0.0001176416 |
39153520600 | 0.111120 | 0.0000987189 |
39153530101 | 0.133256 | 0.0001601361 |
39153530103 | 0.035391 | 0.0001193272 |
39153530104 | 0.045257 | 0.0001895533 |
39153530105 | 0.081395 | 0.0000683501 |
39153530108 | 0.029657 | 0.0001224810 |
39153530401 | 0.191174 | 0.0000941513 |
39153530402 | 0.107411 | 0.0000954835 |
39153530501 | 0.241833 | 0.0001461072 |
39153530502 | 0.221783 | 0.0000867563 |
39153530603 | 0.111472 | 0.0002501277 |
39153530604 | 0.220087 | 0.0000927376 |
39153530605 | 0.201420 | 0.0002645916 |
39153530606 | 0.202064 | 0.0003058083 |
39153530700 | 0.308984 | 0.0000672898 |
39153530800 | 0.303846 | 0.0001754972 |
39153530901 | 0.148399 | 0.0001150588 |
39153530902 | 0.256100 | 0.0001658456 |
39153530903 | 0.311900 | 0.0001336008 |
39153531001 | 0.297294 | 0.0000935532 |
39153531002 | 0.239148 | 0.0001715550 |
39153531101 | 0.251779 | 0.0000754733 |
39153531102 | 0.278946 | 0.0001106543 |
39153531103 | 0.239075 | 0.0000791709 |
39153531401 | 0.201790 | 0.0004110251 |
39153531405 | 0.240563 | 0.0001132100 |
39153531500 | 0.303799 | 0.0004382673 |
39153531601 | 0.329431 | 0.0001141887 |
39153531602 | 0.332257 | 0.0001664981 |
39153531701 | 0.315609 | 0.0002069535 |
39153531702 | 0.293412 | 0.0002281056 |
39153531801 | 0.219328 | 0.0001448838 |
39153531802 | 0.165926 | 0.0001174241 |
39153532001 | 0.302245 | 0.0001026067 |
39153532003 | 0.316235 | 0.0001116603 |
39153532004 | 0.143585 | 0.0001099203 |
39153532202 | 0.107413 | 0.0001752253 |
39153532301 | 0.141417 | 0.0001498319 |
39153532302 | 0.193145 | 0.0001464335 |
39153532501 | 0.274712 | 0.0000876806 |
39153532502 | 0.269937 | 0.0000769143 |
39153532600 | 0.256788 | 0.0001351777 |
39153532701 | 0.095877 | 0.0002052951 |
39153532702 | 0.105848 | 0.0000945592 |
39153532703 | 0.076224 | 0.0001595380 |
39153532705 | 0.120215 | 0.0001894718 |
39153532706 | 0.153172 | 0.0001025796 |
39153532708 | 0.085874 | 0.0001378421 |
39153532901 | 0.219447 | 0.0000378726 |
39153532902 | 0.100274 | 0.0002452067 |
39153532999 | 0.324455 | 0.0002969995 |
39153533000 | 0.237332 | 0.0000488293 |
39153533101 | 0.206093 | 0.0001304742 |
39153533102 | 0.228014 | 0.0000671267 |
39153533200 | 0.172761 | 0.0002956401 |
39153533400 | 0.054816 | 0.0001482551 |
39153533501 | 0.095567 | 0.0002214990 |
39153533502 | 0.216083 | 0.0001039389 |
39153534000 | 0.165254 | 0.0003627940 |
39153534100 | 0.268714 | 0.0000685948 |
39155920300 | 0.179177 | 0.0000764249 |
39155920400 | 0.067206 | 0.0000592150 |
39155920500 | 0.171304 | 0.0000261275 |
39155920600 | 0.511715 | 0.0001073646 |
39155920700 | 0.279355 | 0.0001116875 |
39155920800 | 0.166829 | 0.0000506237 |
39155920900 | 0.158738 | 0.0000893935 |
39155921000 | 0.167789 | 0.0001342533 |
39155921100 | 0.083512 | 0.0000986101 |
39155921200 | 0.113725 | 0.0000471708 |
39155921300 | 0.183770 | 0.0000592694 |
39155921400 | 0.161066 | 0.0000880885 |
39155921500 | 0.185322 | 0.0001479560 |
39155921600 | 0.156779 | 0.0000914869 |
39155930200 | 0.374206 | 0.0000653595 |
39155930300 | 0.312521 | 0.0000877622 |
39155930600 | 0.313353 | 0.0000949126 |
39155930700 | 0.298119 | 0.0001136450 |
39155930800 | 0.273952 | 0.0001250367 |
39155930900 | 0.208888 | 0.0001861005 |
39155931000 | 0.272484 | 0.0001494785 |
39155931100 | 0.355272 | 0.0000666917 |
39155931200 | 0.355779 | 0.0001029058 |
39155931300 | 0.283269 | 0.0001094581 |
39155931400 | 0.280175 | 0.0001162278 |
39155931500 | 0.245631 | 0.0000998064 |
39155931601 | 0.178774 | 0.0001172338 |
39155931602 | 0.192950 | 0.0000750111 |
39155931700 | 0.123209 | 0.0000541853 |
39155931900 | 0.122630 | 0.0001332202 |
39155932000 | 0.119463 | 0.0001438506 |
39155932200 | 0.138488 | 0.0000671810 |
39155932300 | 0.236933 | 0.0001569823 |
39155932500 | 0.289561 | 0.0000812371 |
39155932600 | 0.192990 | 0.0000919491 |
39155932701 | 0.151953 | 0.0001494785 |
39155932702 | 0.180094 | 0.0000643263 |
39155932801 | 0.143269 | 0.0000803128 |
39155932802 | 0.213728 | 0.0000915957 |
39155932900 | 0.110734 | 0.0000659848 |
39155933001 | 0.218009 | 0.0001360205 |
39155933002 | 0.227060 | 0.0001130469 |
39155933100 | 0.282717 | 0.0000668004 |
39155933301 | 0.280986 | 0.0000730264 |
39155933302 | 0.285279 | 0.0001282992 |
39155933400 | 0.236458 | 0.0000872728 |
39155933500 | 0.329839 | 0.0001029058 |
39155933600 | 0.325757 | 0.0001261786 |
39155933700 | 0.239930 | 0.0000698726 |
39155933800 | 0.066793 | 0.0000689211 |
39155933900 | 0.179370 | 0.0000517384 |
39159050601 | 0.321462 | 0.0001626918 |
39165030501 | 0.282133 | 0.0001000783 |
39165030503 | 0.191687 | 0.0001509738 |
39165030504 | 0.216663 | 0.0001207138 |
39165030600 | 0.298080 | 0.0001077724 |
39165030800 | 0.256939 | 0.0001733222 |
39165030900 | 0.178386 | 0.0004080345 |
39165031000 | 0.300628 | 0.0002439833 |
39165031200 | 0.184987 | 0.0001970028 |
39165031300 | 0.217810 | 0.0001302567 |
39165031400 | 0.178152 | 0.0001400987 |
39165031500 | 0.137451 | 0.0001292508 |
39165031600 | 0.256347 | 0.0002093732 |
39165031700 | 0.442380 | 0.0001583961 |
39165031902 | 0.191580 | 0.0002824540 |
39165031903 | 0.255224 | 0.0004472936 |
39165031904 | 0.175586 | 0.0001745728 |
39165032003 | 0.213330 | 0.0002155449 |
39165032004 | 0.170088 | 0.0001545626 |
39165032005 | 0.522890 | 0.0003003708 |
39165032006 | 0.150865 | 0.0001102737 |
39165032007 | 0.125251 | 0.0001840070 |
39165032100 | 0.184237 | 0.0001965406 |
39165032201 | 0.184955 | 0.0005655062 |
39165032202 | 0.240492 | 0.0001594021 |
39165032300 | 0.241890 | 0.0001293323 |
39165032501 | 0.251433 | 0.0000939066 |
39169002500 | 0.331386 | 0.0000713136 |
39169002901 | 0.223336 | 0.0000910247 |
39169002902 | 0.319499 | 0.0001462432 |
39169003000 | 0.271404 | 0.0000620697 |
39169003400 | 0.253991 | 0.0000920307 |
39169003500 | 0.317467 | 0.0000901819 |
39173020100 | 0.229491 | 0.0001432797 |
39173020200 | 0.282728 | 0.0000774308 |
39173020300 | 0.258378 | 0.0001316705 |
39173020401 | 0.178189 | 0.0001399628 |
39173020402 | 0.158452 | 0.0001689993 |
39173020500 | 0.200904 | 0.0000578284 |
39173020601 | 0.157735 | 0.0000974683 |
39173020602 | 0.209541 | 0.0001828651 |
39173020700 | 0.137014 | 0.0001802279 |
39173020800 | 0.306299 | 0.0001160103 |
39173020900 | 0.083839 | 0.0001903690 |
39173021000 | 0.257599 | 0.0001068480 |
39173021200 | 0.230354 | 0.0001784335 |
42003010300 | 0.079758 | 0.0001715006 |
42003020100 | 0.072275 | 0.0001447478 |
42003020300 | 0.190085 | 0.0000324622 |
42003030500 | 0.916080 | 0.0000550825 |
42003040200 | 0.175754 | 0.0000418420 |
42003040400 | 0.327513 | 0.0000502702 |
42003040500 | 0.164000 | 0.0000858591 |
42003040600 | 0.123408 | 0.0000580188 |
42003040900 | 0.029251 | 0.0000903994 |
42003050100 | 1.194189 | 0.0000464911 |
42003050600 | 0.991078 | 0.0000570400 |
42003050900 | 1.573984 | 0.0000354529 |
42003051000 | 0.318179 | 0.0000565778 |
42003051100 | 1.819540 | 0.0000069057 |
42003060300 | 0.129220 | 0.0000592966 |
42003060500 | 0.191179 | 0.0000321088 |
42003070300 | 0.150361 | 0.0000576653 |
42003070500 | 0.313885 | 0.0000829772 |
42003070600 | 0.172653 | 0.0000570400 |
42003070800 | 0.210100 | 0.0000683229 |
42003070900 | 0.386132 | 0.0001120953 |
42003080200 | 0.135518 | 0.0000463824 |
42003080400 | 0.218253 | 0.0000414070 |
42003080600 | 0.116295 | 0.0000561156 |
42003080700 | 0.082297 | 0.0000498896 |
42003080900 | 0.097210 | 0.0000514665 |
42003090100 | 0.207539 | 0.0000523365 |
42003090200 | 0.204561 | 0.0000729177 |
42003090300 | 0.116167 | 0.0000438539 |
42003100500 | 0.668012 | 0.0000498080 |
42003101100 | 0.093674 | 0.0000682686 |
42003101400 | 0.066827 | 0.0000833306 |
42003101600 | 1.144869 | 0.0000271334 |
42003101700 | 0.625986 | 0.0000342838 |
42003101800 | 0.108568 | 0.0000686492 |
42003110200 | 0.050643 | 0.0001022805 |
42003110600 | 0.040667 | 0.0000641360 |
42003111300 | 0.188848 | 0.0000750383 |
42003111400 | 0.474099 | 0.0000372473 |
42003111500 | 0.471895 | 0.0000736789 |
42003120300 | 1.045755 | 0.0000531521 |
42003120400 | 1.432366 | 0.0000174274 |
42003120700 | 1.619703 | 0.0000232184 |
42003120800 | 1.092482 | 0.0000220765 |
42003130100 | 1.768293 | 0.0000454580 |
42003130200 | 1.411009 | 0.0000380357 |
42003130300 | 1.514284 | 0.0000325982 |
42003130400 | 1.494789 | 0.0000225659 |
42003130600 | 1.209366 | 0.0000785455 |
42003140100 | 0.276390 | 0.0001440953 |
42003140200 | 0.232948 | 0.0000645982 |
42003140300 | 0.190968 | 0.0000897469 |
42003140400 | 0.150948 | 0.0000597316 |
42003140500 | 0.143821 | 0.0000501071 |
42003140600 | 0.128900 | 0.0000832490 |
42003140800 | 0.196631 | 0.0001192185 |
42003141000 | 0.241870 | 0.0000256653 |
42003141100 | 0.175940 | 0.0000349907 |
42003141300 | 0.417349 | 0.0001356943 |
42003141400 | 0.084797 | 0.0001383859 |
42003151600 | 0.153160 | 0.0000665014 |
42003151700 | 0.052632 | 0.0001427359 |
42003160800 | 0.043345 | 0.0000686764 |
42003160900 | 0.108629 | 0.0000790349 |
42003170200 | 0.131081 | 0.0000980936 |
42003170600 | 0.033109 | 0.0000453221 |
42003180300 | 0.143447 | 0.0000529618 |
42003180700 | 0.054146 | 0.0000525268 |
42003190300 | 0.266704 | 0.0000488837 |
42003191100 | 0.213112 | 0.0000653323 |
42003191400 | 0.160306 | 0.0000649245 |
42003191500 | 0.197686 | 0.0000510859 |
42003191600 | 0.015538 | 0.0001060868 |
42003191700 | 0.113815 | 0.0000904538 |
42003191800 | 0.100981 | 0.0001364012 |
42003191900 | 0.206343 | 0.0000550009 |
42003192000 | 0.092378 | 0.0000927648 |
42003202200 | 0.198133 | 0.0000787630 |
42003202300 | 0.220179 | 0.0000988005 |
42003210700 | 0.730825 | 0.0000583450 |
42003220600 | 0.024519 | 0.0000479049 |
42003240600 | 0.115922 | 0.0000607103 |
42003241200 | 0.308191 | 0.0000191946 |
42003250300 | 0.206284 | 0.0000313203 |
42003250700 | 0.835450 | 0.0000156602 |
42003250900 | 0.442206 | 0.0000271062 |
42003260200 | 0.192737 | 0.0000553000 |
42003260700 | 0.169584 | 0.0000393951 |
42003260900 | 1.597326 | 0.0000456483 |
42003261200 | 0.279018 | 0.0000272694 |
42003261400 | 0.613937 | 0.0000590247 |
42003261500 | 0.574091 | 0.0000463552 |
42003262000 | 0.130681 | 0.0000617163 |
42003270100 | 0.076440 | 0.0000734342 |
42003270300 | 0.272038 | 0.0000566322 |
42003270400 | 0.247336 | 0.0000249584 |
42003270800 | 0.062082 | 0.0000596772 |
42003271500 | 0.366748 | 0.0000812915 |
42003281400 | 0.201421 | 0.0000633748 |
42003281500 | 0.102587 | 0.0000378454 |
42003290100 | 0.136632 | 0.0000517928 |
42003290200 | 0.256391 | 0.0001212304 |
42003290400 | 0.065363 | 0.0001086152 |
42003300100 | 0.467380 | 0.0000989092 |
42003310200 | 0.151319 | 0.0000873544 |
42003310300 | 0.149467 | 0.0000246865 |
42003320400 | 0.171370 | 0.0000536143 |
42003320600 | 0.161333 | 0.0000580459 |
42003320700 | 0.204089 | 0.0000424945 |
42003401100 | 0.269366 | 0.0001263417 |
42003401200 | 0.130104 | 0.0000688939 |
42003401300 | 0.207994 | 0.0000725642 |
42003402000 | 0.214583 | 0.0000861853 |
42003403500 | 0.132627 | 0.0001144334 |
42003404000 | 0.292259 | 0.0000387154 |
42003405000 | 0.353950 | 0.0000305319 |
42003406000 | 0.334778 | 0.0000631573 |
42003407001 | 0.331251 | 0.0001510010 |
42003407002 | 0.295222 | 0.0001711472 |
42003408001 | 0.271885 | 0.0001506204 |
42003408002 | 0.259558 | 0.0001589127 |
42003409000 | 0.225634 | 0.0003532239 |
42003410000 | 0.243959 | 0.0000331963 |
42003411000 | 0.221157 | 0.0002436842 |
42003412001 | 0.197761 | 0.0002496112 |
42003412002 | 0.247025 | 0.0001371896 |
42003413100 | 0.199804 | 0.0001633715 |
42003413201 | 0.214105 | 0.0000989636 |
42003413202 | 0.249741 | 0.0000743042 |
42003413300 | 0.175060 | 0.0001157928 |
42003413400 | 0.195903 | 0.0001226442 |
42003413500 | 0.138274 | 0.0001812610 |
42003414101 | 0.247480 | 0.0001388753 |
42003414102 | 0.219604 | 0.0001962415 |
42003414200 | 0.209724 | 0.0001563842 |
42003415001 | 0.210363 | 0.0001212848 |
42003415002 | 0.232245 | 0.0000698183 |
42003416000 | 0.302262 | 0.0000427936 |
42003417100 | 0.319068 | 0.0000538318 |
42003417200 | 0.322055 | 0.0000349363 |
42003418000 | 0.345910 | 0.0000461377 |
42003419000 | 0.230648 | 0.0000821887 |
42003420000 | 0.146019 | 0.0000406186 |
42003421100 | 0.266234 | 0.0001238948 |
42003421200 | 0.225298 | 0.0001147325 |
42003422000 | 0.233411 | 0.0001349874 |
42003423000 | 0.203003 | 0.0000734071 |
42003424000 | 0.102037 | 0.0000890672 |
42003425000 | 0.249979 | 0.0000893391 |
42003426300 | 0.352917 | 0.0001586136 |
42003426400 | 0.317216 | 0.0001087240 |
42003426700 | 0.291479 | 0.0000622057 |
42003426800 | 0.248517 | 0.0001449381 |
42003427000 | 0.151436 | 0.0000975498 |
42003427100 | 0.314543 | 0.0001426816 |
42003427200 | 0.238706 | 0.0001304742 |
42003428100 | 0.189445 | 0.0000318641 |
42003428200 | 0.278866 | 0.0000558165 |
42003429100 | 0.176528 | 0.0000711505 |
42003429201 | 0.183427 | 0.0001196535 |
42003429202 | 0.223307 | 0.0001178319 |
42003429300 | 0.209761 | 0.0001546714 |
42003429400 | 0.243427 | 0.0001085065 |
42003429500 | 0.119485 | 0.0001026067 |
42003429600 | 0.235899 | 0.0000901275 |
42003429700 | 0.246904 | 0.0000569312 |
42003430100 | 0.202374 | 0.0000554359 |
42003430200 | 0.281050 | 0.0001201429 |
42003431100 | 0.100245 | 0.0000804487 |
42003431400 | 0.095983 | 0.0000494002 |
42003431500 | 0.163095 | 0.0000850434 |
42003432300 | 0.138808 | 0.0000555175 |
42003432400 | 0.136826 | 0.0000620697 |
42003434000 | 0.275066 | 0.0000499440 |
42003435000 | 0.180481 | 0.0000646254 |
42003437000 | 0.184121 | 0.0001744913 |
42003439000 | 0.256152 | 0.0000387970 |
42003445500 | 0.104231 | 0.0001011658 |
42003446000 | 0.270257 | 0.0000429023 |
42003447000 | 0.191725 | 0.0000429295 |
42003448000 | 0.088012 | 0.0000298250 |
42003449000 | 0.220745 | 0.0000678336 |
42003450700 | 0.115518 | 0.0000760715 |
42003450800 | 0.050101 | 0.0000661479 |
42003451101 | 0.220481 | 0.0000988005 |
42003451102 | 0.125463 | 0.0001431437 |
42003451104 | 0.230307 | 0.0001024980 |
42003451105 | 0.167679 | 0.0001276195 |
42003451300 | 0.161710 | 0.0001980087 |
42003452000 | 0.294806 | 0.0001541276 |
42003453003 | 0.299135 | 0.0000519831 |
42003453004 | 0.131669 | 0.0001709297 |
42003455000 | 0.316671 | 0.0000405370 |
42003456001 | 0.265161 | 0.0001057877 |
42003456003 | 0.304192 | 0.0001874055 |
42003456004 | 0.186858 | 0.0001273476 |
42003457100 | 0.227043 | 0.0000377367 |
42003457200 | 0.229290 | 0.0000930366 |
42003458000 | 0.211638 | 0.0002170130 |
42003459101 | 0.204515 | 0.0000459746 |
42003459102 | 0.216712 | 0.0001629093 |
42003459201 | 0.164132 | 0.0001608974 |
42003459202 | 0.192944 | 0.0000184877 |
42003460001 | 0.350994 | 0.0001230792 |
42003460002 | 0.238218 | 0.0000926288 |
42003461000 | 0.111014 | 0.0000262906 |
42003462100 | 0.172563 | 0.0000724283 |
42003462600 | 0.156852 | 0.0000836840 |
42003463900 | 0.133960 | 0.0000686764 |
42003464300 | 0.118985 | 0.0000876535 |
42003464400 | 0.175693 | 0.0000837112 |
42003465600 | 0.158920 | 0.0000709873 |
42003465800 | 0.196644 | 0.0000850162 |
42003468700 | 0.157327 | 0.0000407273 |
42003468800 | 0.156226 | 0.0000723739 |
42003468900 | 0.057779 | 0.0000954564 |
42003469000 | 0.201996 | 0.0001315617 |
42003470300 | 0.155220 | 0.0001042924 |
42003470400 | 0.248571 | 0.0000756636 |
42003470501 | 0.703255 | 0.0000915141 |
42003470502 | 0.145825 | 0.0000799049 |
42003470600 | 0.281373 | 0.0000786543 |
42003471000 | 0.244779 | 0.0000339576 |
42003472100 | 0.233126 | 0.0000586985 |
42003472200 | 0.179194 | 0.0000627222 |
42003472300 | 0.078093 | 0.0000526356 |
42003472400 | 0.279569 | 0.0000481496 |
42003473100 | 0.238410 | 0.0001349330 |
42003473200 | 0.180234 | 0.0000757452 |
42003473300 | 0.239426 | 0.0001431437 |
42003473401 | 0.275976 | 0.0000948310 |
42003473402 | 0.264055 | 0.0000898285 |
42003473500 | 0.288760 | 0.0000995889 |
42003473601 | 0.179409 | 0.0001003502 |
42003473602 | 0.178138 | 0.0001215023 |
42003474101 | 0.264214 | 0.0001002142 |
42003474102 | 0.256598 | 0.0000999152 |
42003474201 | 0.228252 | 0.0000689211 |
42003474202 | 0.269359 | 0.0001332746 |
42003474203 | 0.218677 | 0.0001264504 |
42003475101 | 0.126543 | 0.0001255532 |
42003475102 | 0.335236 | 0.0000428752 |
42003475200 | 0.250227 | 0.0001319696 |
42003475301 | 0.188831 | 0.0001224266 |
42003475303 | 0.311490 | 0.0001070655 |
42003475304 | 0.198686 | 0.0001396093 |
42003475401 | 0.270380 | 0.0001038846 |
42003475402 | 0.268042 | 0.0000779746 |
42003476100 | 0.127480 | 0.0001335465 |
42003476200 | 0.318415 | 0.0000825422 |
42003477100 | 0.251068 | 0.0000873000 |
42003477200 | 0.297893 | 0.0001098115 |
42003477300 | 0.163495 | 0.0001521157 |
42003478100 | 0.084578 | 0.0001064946 |
42003478200 | 0.157921 | 0.0001444488 |
42003479000 | 0.320597 | 0.0000539134 |
42003480101 | 0.194829 | 0.0001435788 |
42003480102 | 0.240755 | 0.0000778930 |
42003480200 | 0.107641 | 0.0000935532 |
42003480300 | 0.222414 | 0.0000902635 |
42003480400 | 0.141054 | 0.0001218013 |
42003481000 | 0.106742 | 0.0000849891 |
42003482500 | 0.123488 | 0.0000453764 |
42003483800 | 0.501341 | 0.0000849075 |
42003484300 | 0.187426 | 0.0000825693 |
42003484500 | 0.221500 | 0.0001622024 |
42003484600 | 0.082067 | 0.0000517112 |
42003485000 | 0.104813 | 0.0000301513 |
42003486700 | 0.386691 | 0.0000519287 |
42003486800 | 0.751396 | 0.0000424673 |
42003486900 | 0.819933 | 0.0000381173 |
42003487000 | 0.225579 | 0.0000470349 |
42003488100 | 0.113815 | 0.0000551097 |
42003488200 | 0.148227 | 0.0000875175 |
42003488300 | 0.283386 | 0.0000554359 |
42003488400 | 0.170645 | 0.0001168260 |
42003488500 | 0.271529 | 0.0000713136 |
42003488600 | 0.182813 | 0.0001265320 |
42003489001 | 0.198539 | 0.0001246832 |
42003489002 | 0.298273 | 0.0000944504 |
42003490002 | 0.103694 | 0.0001264776 |
42003490003 | 0.165280 | 0.0000979576 |
42003490004 | 0.207973 | 0.0001307733 |
42003491101 | 0.236827 | 0.0001886289 |
42003491200 | 0.219038 | 0.0000506781 |
42003492700 | 0.137141 | 0.0000600307 |
42003492800 | 0.353075 | 0.0000601666 |
42003492900 | 0.207946 | 0.0000568225 |
42003494000 | 0.247711 | 0.0000388242 |
42003495000 | 0.316317 | 0.0000887682 |
42003496101 | 0.306613 | 0.0000805846 |
42003496102 | 0.251283 | 0.0001164453 |
42003496200 | 0.285188 | 0.0001540732 |
42003497000 | 0.308219 | 0.0000273237 |
42003498000 | 0.275347 | 0.0000629669 |
42003499300 | 0.323194 | 0.0000474699 |
42003499400 | 0.075310 | 0.0000678336 |
42003500300 | 0.201481 | 0.0000984198 |
42003501000 | 0.192008 | 0.0000435005 |
42003503002 | 0.229167 | 0.0001600546 |
42003504100 | 0.047961 | 0.0001248192 |
42003507000 | 0.244084 | 0.0000490740 |
42003508000 | 0.163940 | 0.0000454580 |
42003509400 | 0.095410 | 0.0001310724 |
42003510000 | 0.837291 | 0.0000415430 |
42003512000 | 0.154656 | 0.0000601938 |
42003512800 | 0.679053 | 0.0000346644 |
42003512900 | 0.502561 | 0.0000274053 |
42003513800 | 0.812814 | 0.0000461377 |
42003514000 | 1.152661 | 0.0000551640 |
42003515100 | 0.431460 | 0.0000747121 |
42003515200 | 0.040171 | 0.0000544028 |
42003515300 | 0.325370 | 0.0000431742 |
42003515401 | 0.127985 | 0.0000598947 |
42003516100 | 0.182886 | 0.0000359695 |
42003516200 | 0.050067 | 0.0000442617 |
42003517000 | 0.149789 | 0.0000433102 |
42003518001 | 0.236265 | 0.0000824334 |
42003519000 | 0.093057 | 0.0000775124 |
42003520001 | 0.161967 | 0.0000814546 |
42003520002 | 0.096278 | 0.0000773493 |
42003521100 | 0.061406 | 0.0001113612 |
42003521200 | 0.034294 | 0.0001108446 |
42003521301 | 0.038489 | 0.0001093493 |
42003521302 | 0.115924 | 0.0001194088 |
42003521401 | 0.108120 | 0.0000795787 |
42003521402 | 0.131281 | 0.0000935804 |
42003521500 | 0.136209 | 0.0001016280 |
42003522000 | 0.039471 | 0.0000833306 |
42003523100 | 1.125352 | 0.0000888497 |
42003523200 | 0.699637 | 0.0001064674 |
42003523300 | 0.250639 | 0.0001042380 |
42003523400 | 0.244943 | 0.0001257436 |
42003523501 | 0.275088 | 0.0001107359 |
42003523502 | 0.170733 | 0.0000396942 |
42003523600 | 0.152657 | 0.0001244114 |
42003523701 | 0.161011 | 0.0000986645 |
42003523702 | 0.153192 | 0.0001381412 |
42003523800 | 0.165662 | 0.0001237588 |
42003524000 | 0.140938 | 0.0000721292 |
42003525100 | 0.183184 | 0.0000491827 |
42003525200 | 0.334583 | 0.0000606832 |
42003525300 | 0.275583 | 0.0000631573 |
42003526101 | 0.207237 | 0.0001964046 |
42003526102 | 0.374206 | 0.0000568769 |
42003526201 | 0.235854 | 0.0000993170 |
42003526202 | 0.146821 | 0.0001205507 |
42003526301 | 0.334767 | 0.0001088871 |
42003526302 | 0.227109 | 0.0001364556 |
42003550900 | 0.778005 | 0.0000468718 |
42003551200 | 0.128700 | 0.0000891760 |
42003551300 | 0.189881 | 0.0000708242 |
42003551900 | 0.200643 | 0.0000374376 |
42003552000 | 0.398147 | 0.0000637554 |
42003552100 | 0.413869 | 0.0000395854 |
42003552200 | 0.135859 | 0.0000232999 |
42003552300 | 0.460380 | 0.0000430927 |
42003552400 | 0.090007 | 0.0000898557 |
42003560400 | 0.283050 | 0.0000448871 |
42003560500 | 0.139845 | 0.0000645438 |
42003560600 | 0.790756 | 0.0000222396 |
42003561000 | 0.909901 | 0.0000334682 |
42003561100 | 1.318080 | 0.0000210434 |
42003561200 | 1.156813 | 0.0000396942 |
42003561400 | 0.693634 | 0.0001064402 |
42003561500 | 0.588296 | 0.0000681870 |
42003561600 | 0.181444 | 0.0000538318 |
42003561700 | 0.136338 | 0.0000193305 |
42003561900 | 1.106049 | 0.0000660935 |
42003562000 | 0.262700 | 0.0000766696 |
42003562300 | 0.352227 | 0.0000788446 |
42003562400 | 0.226299 | 0.0000664470 |
42003562500 | 0.428950 | 0.0000616075 |
42003562600 | 0.116000 | 0.0000642176 |
42003562700 | 0.072543 | 0.0000494002 |
42003562800 | 0.155509 | 0.0000398301 |
42003562900 | 0.104830 | 0.0000460833 |
42003563000 | 0.163222 | 0.0000774580 |
42003563100 | 0.110502 | 0.0000930095 |
42003563200 | 0.059713 | 0.0000539950 |
42003563300 | 0.204904 | 0.0000384707 |
42003563800 | 0.239776 | 0.0001023349 |
42003563900 | 0.080519 | 0.0000980664 |
42003564000 | 0.303288 | 0.0001752525 |
42003564100 | 0.285225 | 0.0000235446 |
42003564200 | 0.187772 | 0.0000541037 |
42003564400 | 0.136109 | 0.0001567105 |
42003564500 | 0.297511 | 0.0000778115 |
42003980500 | 0.374206 | 0.0000004350 |
42003980600 | 0.374206 | 0.0000003534 |
42003980900 | 0.373491 | 0.0000343110 |
42003981800 | 0.054936 | 0.0000054104 |
42003982200 | 0.135369 | 0.0001223179 |
42005951200 | 0.279934 | 0.0001572270 |
42005951300 | 0.276697 | 0.0000685676 |
42005951400 | 0.217632 | 0.0000699814 |
42005951500 | 0.171454 | 0.0000698183 |
42005951600 | 0.374206 | 0.0001211488 |
42005951800 | 0.294757 | 0.0000551912 |
42005951900 | 0.328296 | 0.0000476330 |
42007600601 | 0.359700 | 0.0000571759 |
42007600602 | 0.310362 | 0.0000709873 |
42007600700 | 0.278857 | 0.0002024947 |
42007601000 | 0.228125 | 0.0000896110 |
42007601100 | 0.050475 | 0.0000752830 |
42007601200 | 0.127204 | 0.0000618522 |
42007601300 | 0.153565 | 0.0000737605 |
42007601400 | 0.146142 | 0.0000912966 |
42007601600 | 0.141930 | 0.0000325438 |
42007601700 | 0.345562 | 0.0000880613 |
42007601800 | 0.329221 | 0.0001934140 |
42007602100 | 0.064648 | 0.0000902635 |
42007602300 | 0.248834 | 0.0000650332 |
42007602400 | 0.210335 | 0.0000516296 |
42007602500 | 0.321888 | 0.0000350723 |
42007602601 | 0.189068 | 0.0001331386 |
42007602602 | 0.277509 | 0.0000899916 |
42007602701 | 0.257616 | 0.0000455667 |
42007603000 | 0.315644 | 0.0000796331 |
42007603202 | 0.243097 | 0.0001856111 |
42007603300 | 0.222080 | 0.0000957282 |
42007603400 | 0.252947 | 0.0000455939 |
42007603500 | 0.195784 | 0.0000400476 |
42007603600 | 0.326807 | 0.0000564962 |
42007603700 | 0.282461 | 0.0001044283 |
42007603801 | 0.267262 | 0.0000800409 |
42007603802 | 0.322851 | 0.0000835481 |
42007603803 | 0.312224 | 0.0000852609 |
42007603900 | 0.238925 | 0.0000824334 |
42007604000 | 0.101606 | 0.0000627222 |
42007604100 | 0.046199 | 0.0000713680 |
42007604200 | 0.162847 | 0.0000404826 |
42007604500 | 0.608926 | 0.0000614444 |
42007604600 | 0.143039 | 0.0000718302 |
42007604700 | 0.073552 | 0.0000341207 |
42007604800 | 0.268002 | 0.0001137266 |
42007604901 | 0.165406 | 0.0001118506 |
42007604902 | 0.148383 | 0.0001128022 |
42007605001 | 0.268960 | 0.0000659848 |
42007605100 | 0.349287 | 0.0001272117 |
42007605200 | 0.161700 | 0.0000666917 |
42007605300 | 0.289225 | 0.0000772677 |
42007605400 | 0.191072 | 0.0000895294 |
42007605500 | 0.252450 | 0.0001367546 |
42007605600 | 0.155192 | 0.0000831403 |
42007605700 | 0.231433 | 0.0000655226 |
42007605800 | 0.320798 | 0.0001690809 |
42011000100 | 0.827703 | 0.0001302567 |
42011000200 | 0.967902 | 0.0001066034 |
42011000300 | 0.797426 | 0.0000633204 |
42011000400 | 0.928810 | 0.0000985014 |
42011000500 | 1.269840 | 0.0001112525 |
42011000600 | 0.239539 | 0.0000906713 |
42011000700 | 1.173341 | 0.0001216926 |
42011000800 | 1.325862 | 0.0001209041 |
42011000900 | 0.698018 | 0.0000653595 |
42011001000 | 1.410360 | 0.0000778115 |
42011001100 | 1.366915 | 0.0001062499 |
42011001200 | 1.350415 | 0.0000454036 |
42011001300 | 1.472010 | 0.0000899644 |
42011001400 | 1.475755 | 0.0001015736 |
42011001500 | 1.329753 | 0.0000961632 |
42011001600 | 1.161089 | 0.0000816993 |
42011001700 | 1.580796 | 0.0000875447 |
42011001800 | 0.298415 | 0.0000702805 |
42011001900 | 0.626406 | 0.0000578556 |
42011002000 | 0.684036 | 0.0001155481 |
42011002100 | 1.068528 | 0.0000696279 |
42011002200 | 1.467472 | 0.0000585081 |
42011002300 | 1.147423 | 0.0000701173 |
42011002500 | 1.176246 | 0.0000786543 |
42011002600 | 1.132102 | 0.0000904266 |
42011002700 | 0.083689 | 0.0000535056 |
42011002900 | 0.214021 | 0.0000908616 |
42011010201 | 0.281922 | 0.0001193816 |
42011010202 | 0.227399 | 0.0001392015 |
42011010303 | 0.202283 | 0.0000580188 |
42011010304 | 0.093320 | 0.0001815329 |
42011010400 | 0.199855 | 0.0002275619 |
42011010500 | 0.164919 | 0.0003521907 |
42011010600 | 0.154473 | 0.0002329722 |
42011010700 | 0.090964 | 0.0003937337 |
42011010801 | 0.256653 | 0.0001002142 |
42011010802 | 0.060015 | 0.0002486052 |
42011010902 | 0.075570 | 0.0001097843 |
42011010903 | 0.096096 | 0.0001690265 |
42011010904 | 0.116176 | 0.0001031233 |
42011010905 | 0.115829 | 0.0001253357 |
42011011000 | 0.076389 | 0.0001150044 |
42011011101 | 0.082941 | 0.0000547018 |
42011011102 | 0.156693 | 0.0001505388 |
42011011200 | 0.128958 | 0.0001087512 |
42011011300 | 0.153985 | 0.0000757724 |
42011011400 | 0.202786 | 0.0001390112 |
42011011500 | 0.218200 | 0.0000814003 |
42011011601 | 0.047182 | 0.0001388209 |
42011011602 | 0.110882 | 0.0001093493 |
42011011603 | 0.137906 | 0.0001643774 |
42011011701 | 0.237224 | 0.0003952562 |
42011011702 | 0.264801 | 0.0002495296 |
42011011800 | 0.216136 | 0.0001369721 |
42011011902 | 0.219448 | 0.0000983383 |
42011011903 | 0.171410 | 0.0001330843 |
42011011904 | 0.087448 | 0.0002158167 |
42011012001 | 0.098545 | 0.0001235413 |
42011012002 | 0.082848 | 0.0002539340 |
42011012101 | 0.117896 | 0.0000539134 |
42011012103 | 0.226396 | 0.0000641360 |
42011012104 | 0.072907 | 0.0000816993 |
42011012105 | 0.099105 | 0.0002254140 |
42011012200 | 0.130223 | 0.0000821071 |
42011012300 | 0.139831 | 0.0001209041 |
42011012400 | 0.171728 | 0.0001896349 |
42011012500 | 0.363049 | 0.0000571759 |
42011012600 | 0.316349 | 0.0000608191 |
42011012700 | 0.032936 | 0.0002341413 |
42011012800 | 0.163063 | 0.0001041564 |
42011012900 | 0.225703 | 0.0002094276 |
42011013000 | 0.199570 | 0.0001832457 |
42011013100 | 0.342708 | 0.0001381140 |
42011013200 | 0.091814 | 0.0001101378 |
42011013301 | 0.249698 | 0.0000809924 |
42011013302 | 0.305565 | 0.0001770741 |
42011013401 | 0.363436 | 0.0002158167 |
42011013500 | 0.093995 | 0.0003249757 |
42011013600 | 0.196484 | 0.0001104368 |
42011013701 | 0.254706 | 0.0000931454 |
42011013702 | 0.264535 | 0.0001036399 |
42011013800 | 0.249680 | 0.0001156569 |
42011013900 | 0.296407 | 0.0002148652 |
42011014100 | 0.092437 | 0.0002066001 |
42011014200 | 0.262723 | 0.0002021956 |
42017100102 | 0.196521 | 0.0000759355 |
42017100103 | 0.086730 | 0.0000627766 |
42017100104 | 0.255054 | 0.0001204419 |
42017100105 | 0.139046 | 0.0000859134 |
42017100201 | 0.119636 | 0.0001247376 |
42017100206 | 0.112064 | 0.0001381684 |
42017100207 | 0.100708 | 0.0001130740 |
42017100208 | 0.101556 | 0.0001437691 |
42017100209 | 0.153677 | 0.0002430589 |
42017100210 | 0.083912 | 0.0001923808 |
42017100211 | 0.064290 | 0.0001868889 |
42017100212 | 0.054594 | 0.0000976314 |
42017100302 | 0.206518 | 0.0001359390 |
42017100303 | 0.088226 | 0.0001283808 |
42017100304 | 0.054907 | 0.0000634019 |
42017100306 | 0.026028 | 0.0000932270 |
42017100307 | 0.034898 | 0.0001339271 |
42017100401 | 0.078031 | 0.0001713919 |
42017100402 | 0.079624 | 0.0001728872 |
42017100403 | 0.119006 | 0.0000613629 |
42017100404 | 0.056792 | 0.0001794938 |
42017100406 | 0.086485 | 0.0000929279 |
42017100407 | 0.210609 | 0.0000285744 |
42017100408 | 0.132765 | 0.0001711744 |
42017100500 | 0.225840 | 0.0000620969 |
42017100600 | 0.059786 | 0.0000985286 |
42017100700 | 0.042874 | 0.0000855328 |
42017100803 | 0.161965 | 0.0001215023 |
42017100804 | 0.137777 | 0.0000996705 |
42017100805 | 0.159984 | 0.0001776179 |
42017100807 | 0.133438 | 0.0001174241 |
42017100808 | 0.219069 | 0.0001353952 |
42017100809 | 0.106051 | 0.0001511641 |
42017100811 | 0.091671 | 0.0001233238 |
42017100900 | 0.209698 | 0.0002040172 |
42017101100 | 0.007981 | 0.0000740867 |
42017101401 | 0.186878 | 0.0001314258 |
42017101403 | 0.241145 | 0.0001425456 |
42017101404 | 0.236765 | 0.0000626135 |
42017101405 | 0.222980 | 0.0001768294 |
42017101503 | 0.306277 | 0.0001006764 |
42017101504 | 0.244787 | 0.0000707426 |
42017101505 | 0.264282 | 0.0000892303 |
42017101506 | 0.307849 | 0.0001437419 |
42017101603 | 0.129189 | 0.0000951845 |
42017101605 | 0.092684 | 0.0001093493 |
42017101607 | 0.174609 | 0.0000965982 |
42017101609 | 0.205430 | 0.0001127478 |
42017101610 | 0.170469 | 0.0001328124 |
42017101611 | 0.240460 | 0.0001734581 |
42017101802 | 0.191194 | 0.0001728056 |
42017101803 | 0.183662 | 0.0002468380 |
42017101805 | 0.201296 | 0.0000588888 |
42017101807 | 0.089814 | 0.0001094581 |
42017101808 | 0.187461 | 0.0000679695 |
42017101900 | 0.211816 | 0.0001122312 |
42017102002 | 0.236384 | 0.0000716127 |
42017102003 | 0.199253 | 0.0001163094 |
42017102004 | 0.169215 | 0.0001190282 |
42017102102 | 0.239340 | 0.0000791165 |
42017102104 | 0.145145 | 0.0001575805 |
42017102300 | 0.222973 | 0.0003084184 |
42017102401 | 0.215346 | 0.0001037758 |
42017102402 | 0.205723 | 0.0001262873 |
42017102500 | 0.163818 | 0.0001116603 |
42017102600 | 0.170001 | 0.0000578013 |
42017102700 | 0.234319 | 0.0002619272 |
42017102801 | 0.254033 | 0.0001877589 |
42017103101 | 0.082796 | 0.0000564691 |
42017103102 | 0.112488 | 0.0000528259 |
42017103103 | 0.138029 | 0.0001240851 |
42017103400 | 0.266213 | 0.0001348787 |
42017104000 | 0.283355 | 0.0001918915 |
42017104100 | 0.083112 | 0.0000590791 |
42017104201 | 0.267195 | 0.0000808293 |
42017104203 | 0.173603 | 0.0001558133 |
42017104204 | 0.170037 | 0.0001384946 |
42017104301 | 0.312671 | 0.0000709873 |
42017104303 | 0.227835 | 0.0001261242 |
42017104304 | 0.219537 | 0.0000328700 |
42017104400 | 0.204729 | 0.0000669635 |
42017104502 | 0.241565 | 0.0002091285 |
42017104503 | 0.244285 | 0.0001138897 |
42017104505 | 0.195305 | 0.0001535839 |
42017104506 | 0.180118 | 0.0000620154 |
42017104601 | 0.257961 | 0.0001210129 |
42017104603 | 0.134939 | 0.0001908855 |
42017104604 | 0.273141 | 0.0001549976 |
42017104701 | 0.189989 | 0.0000895294 |
42017104702 | 0.198701 | 0.0000685676 |
42017104703 | 0.234349 | 0.0000633748 |
42017104800 | 0.207741 | 0.0000800681 |
42017104901 | 0.280614 | 0.0001937402 |
42017104902 | 0.247364 | 0.0002010538 |
42017105003 | 0.233641 | 0.0001309364 |
42017105004 | 0.137982 | 0.0001529314 |
42017105006 | 0.230347 | 0.0001500766 |
42017105008 | 0.212084 | 0.0000974683 |
42017105009 | 0.207440 | 0.0000958370 |
42017105010 | 0.143693 | 0.0001032321 |
42017105011 | 0.171179 | 0.0000875447 |
42017105012 | 0.277704 | 0.0000776483 |
42017105013 | 0.211072 | 0.0001561667 |
42017105100 | 0.199520 | 0.0000822975 |
42017105202 | 0.208241 | 0.0001305014 |
42017105203 | 0.219209 | 0.0000553815 |
42017105206 | 0.124555 | 0.0001431166 |
42017105207 | 0.140338 | 0.0001350962 |
42017105208 | 0.249935 | 0.0000600850 |
42017105300 | 0.318199 | 0.0000520646 |
42017105400 | 0.153733 | 0.0002188890 |
42017105505 | 0.188515 | 0.0001064130 |
42017105506 | 0.136792 | 0.0001092678 |
42017105507 | 0.184122 | 0.0001809348 |
42017105508 | 0.172517 | 0.0000941242 |
42017105509 | 0.168228 | 0.0001155481 |
42017105510 | 0.060715 | 0.0001448838 |
42017105511 | 0.160134 | 0.0001135091 |
42017105600 | 0.178709 | 0.0000662295 |
42017105702 | 0.022698 | 0.0001598642 |
42017105704 | 0.032066 | 0.0001753613 |
42017105801 | 0.006343 | 0.0001564386 |
42017105805 | 0.080644 | 0.0001527139 |
42017105807 | 0.069108 | 0.0001018999 |
42017105808 | 0.177185 | 0.0000908072 |
42017105809 | 0.141220 | 0.0001085065 |
42017105810 | 0.148854 | 0.0000588616 |
42017105811 | 0.088593 | 0.0001537470 |
42017105812 | 0.130730 | 0.0000423042 |
42017105900 | 0.220449 | 0.0000589160 |
42017106000 | 0.210696 | 0.0001070112 |
42017106100 | 0.144401 | 0.0000867563 |
42017106200 | 0.114054 | 0.0001727784 |
42017106300 | 0.216178 | 0.0001959968 |
42017106401 | 0.225537 | 0.0004058594 |
42017106402 | 0.251983 | 0.0002011081 |
42017106500 | 0.223516 | 0.0001735397 |
42019911400 | 0.330995 | 0.0000929279 |
42019911501 | 0.351104 | 0.0001442856 |
42019911502 | 0.309490 | 0.0001188379 |
42019911700 | 0.319148 | 0.0001276467 |
42019911800 | 0.307260 | 0.0001760954 |
42019911900 | 0.332971 | 0.0001274564 |
42019912001 | 0.199448 | 0.0001368090 |
42019912002 | 0.177505 | 0.0001562755 |
42019912101 | 0.244097 | 0.0001132100 |
42019912102 | 0.228685 | 0.0000710145 |
42019912200 | 0.136296 | 0.0000892575 |
42019912301 | 0.190029 | 0.0001614139 |
42019912303 | 0.227568 | 0.0000728089 |
42019912304 | 0.269502 | 0.0000968429 |
42019912401 | 0.253890 | 0.0002410198 |
42019912402 | 0.297137 | 0.0001875142 |
42019912700 | 0.308578 | 0.0001971387 |
42019912800 | 0.297382 | 0.0001504845 |
42025020500 | 0.234257 | 0.0001893630 |
42025020600 | 0.143185 | 0.0001434700 |
42025020700 | 0.258187 | 0.0001341174 |
42025020800 | 0.288335 | 0.0002303622 |
42025020900 | 0.348630 | 0.0001444488 |
42029300101 | 0.171057 | 0.0000808837 |
42029300103 | 0.150806 | 0.0000666373 |
42029300104 | 0.174496 | 0.0001356943 |
42029300106 | 0.475230 | 0.0001244114 |
42029300107 | 0.355269 | 0.0001180222 |
42029300108 | 0.288547 | 0.0001662806 |
42029300109 | 0.128865 | 0.0000912966 |
42029300201 | 0.170896 | 0.0001410503 |
42029300202 | 0.229308 | 0.0001381140 |
42029300301 | 0.196243 | 0.0001091046 |
42029300302 | 0.299102 | 0.0001012474 |
42029300303 | 0.121147 | 0.0000823246 |
42029300400 | 0.145503 | 0.0000907257 |
42029300501 | 0.176916 | 0.0001319152 |
42029300502 | 0.137605 | 0.0000954835 |
42029300600 | 0.020411 | 0.0001447206 |
42029300700 | 0.120118 | 0.0001327036 |
42029300800 | 0.106772 | 0.0001116331 |
42029300900 | 0.115216 | 0.0000646798 |
42029301000 | 0.154478 | 0.0001989603 |
42029301100 | 0.230218 | 0.0000886866 |
42029301300 | 0.126150 | 0.0003649146 |
42029301401 | 0.122123 | 0.0000751743 |
42029301402 | 0.247132 | 0.0001374887 |
42029301500 | 0.247112 | 0.0000715583 |
42029301700 | 0.212751 | 0.0000448327 |
42029301800 | 0.183091 | 0.0001452644 |
42029301900 | 0.302709 | 0.0001106000 |
42029302000 | 0.113915 | 0.0001572814 |
42029302101 | 0.238817 | 0.0001965134 |
42029302102 | 0.064379 | 0.0001198710 |
42029302202 | 0.332875 | 0.0001998575 |
42029302203 | 0.147473 | 0.0001347427 |
42029302204 | 0.076286 | 0.0001658999 |
42029302300 | 0.090889 | 0.0000808021 |
42029302400 | 0.072474 | 0.0001203604 |
42029302500 | 0.203287 | 0.0001161735 |
42029302600 | 0.059306 | 0.0001315074 |
42029302702 | 0.220877 | 0.0001281905 |
42029302703 | 0.198807 | 0.0001172338 |
42029302704 | 0.166974 | 0.0001328668 |
42029302705 | 0.114571 | 0.0001037486 |
42029302706 | 0.249706 | 0.0001278642 |
42029302802 | 0.283055 | 0.0001346883 |
42029302803 | 0.374206 | 0.0000552184 |
42029302804 | 0.232943 | 0.0001072015 |
42029302805 | 0.116595 | 0.0001960784 |
42029302901 | 0.203281 | 0.0001227529 |
42029302902 | 0.147742 | 0.0001700597 |
42029303000 | 0.132929 | 0.0000840919 |
42029303100 | 0.152304 | 0.0001123400 |
42029303301 | 0.213515 | 0.0000917860 |
42029303302 | 0.143964 | 0.0001287342 |
42029303401 | 0.324107 | 0.0001104640 |
42029303402 | 0.329060 | 0.0000576653 |
42029303501 | 0.143367 | 0.0001190825 |
42029303502 | 0.174868 | 0.0000772677 |
42029303801 | 0.166342 | 0.0001154938 |
42029303802 | 0.133938 | 0.0002293563 |
42029303901 | 0.105973 | 0.0001225898 |
42029303902 | 0.194709 | 0.0001391743 |
42029304000 | 0.253928 | 0.0001284623 |
42029304101 | 0.058745 | 0.0001129653 |
42029304102 | 0.008954 | 0.0000972507 |
42029304201 | 0.108548 | 0.0001886017 |
42029304300 | 0.117497 | 0.0002259578 |
42029304403 | 0.217297 | 0.0001066305 |
42029304404 | 0.044450 | 0.0001347427 |
42029304405 | 0.180223 | 0.0001729959 |
42029304406 | 0.237243 | 0.0000959729 |
42029304501 | 0.414740 | 0.0002301991 |
42029304502 | 0.273301 | 0.0000799321 |
42029304600 | 0.171082 | 0.0000988820 |
42029304900 | 0.211753 | 0.0002240274 |
42029305000 | 0.238120 | 0.0000527987 |
42029305101 | 0.155242 | 0.0001167716 |
42029305102 | 0.134264 | 0.0001235957 |
42029305300 | 0.022328 | 0.0001928159 |
42029305400 | 0.246118 | 0.0001111437 |
42029305500 | 0.791573 | 0.0000968973 |
42029305600 | 0.758383 | 0.0000719389 |
42029305700 | 0.345612 | 0.0000609550 |
42029306000 | 0.092322 | 0.0002010538 |
42029306300 | 0.391527 | 0.0000764521 |
42029306501 | 0.082815 | 0.0001130197 |
42029306503 | 0.529225 | 0.0000823790 |
42029306504 | 0.243738 | 0.0001294683 |
42029306600 | 0.289548 | 0.0000863213 |
42029306700 | 0.208940 | 0.0001218557 |
42029306800 | 0.250598 | 0.0000475515 |
42029306900 | 0.186206 | 0.0001596196 |
42029307000 | 0.152286 | 0.0001471132 |
42029307100 | 0.132018 | 0.0000647613 |
42029307200 | 0.141122 | 0.0000352082 |
42029307300 | 0.052312 | 0.0001048361 |
42029307400 | 0.097680 | 0.0000964351 |
42029307700 | 0.253657 | 0.0000704164 |
42029307800 | 0.092557 | 0.0000676976 |
42029307900 | 0.038296 | 0.0001324861 |
42029308000 | 0.280617 | 0.0001450741 |
42029308101 | 0.206204 | 0.0001240851 |
42029308102 | 0.103361 | 0.0001160919 |
42029308200 | 0.184719 | 0.0000736246 |
42029310400 | 0.026541 | 0.0000830315 |
42029311000 | 0.098516 | 0.0003776385 |
42029311100 | 0.267323 | 0.0000979033 |
42029311200 | 0.213524 | 0.0000564962 |
42029311300 | 0.050224 | 0.0001257707 |
42029311401 | 0.015193 | 0.0001869161 |
42029311403 | 0.199996 | 0.0000987733 |
42029311404 | 0.167157 | 0.0001014649 |
42029311500 | 0.261053 | 0.0000913238 |
42029311600 | 0.163074 | 0.0000598403 |
42029311700 | 0.133430 | 0.0002709808 |
42029311800 | 0.156026 | 0.0000970061 |
42041010100 | 0.136315 | 0.0001500223 |
42041010201 | 0.142948 | 0.0001423009 |
42041010203 | 0.147455 | 0.0001067393 |
42041010204 | 0.151717 | 0.0001368634 |
42041010300 | 0.090951 | 0.0001111709 |
42041010400 | 0.231382 | 0.0000989092 |
42041010500 | 0.096536 | 0.0001112525 |
42041010600 | 0.050072 | 0.0001195447 |
42041010700 | 0.271476 | 0.0000979576 |
42041010800 | 0.157680 | 0.0000965711 |
42041010900 | 0.269382 | 0.0001187563 |
42041011002 | 0.040199 | 0.0000606560 |
42041011101 | 0.221417 | 0.0001129653 |
42041011102 | 0.166021 | 0.0001139712 |
42041011200 | 0.167831 | 0.0000407273 |
42041011301 | 0.212715 | 0.0001297130 |
42041011302 | 0.238414 | 0.0002050504 |
42041011303 | 0.236467 | 0.0001734038 |
42041011304 | 0.147306 | 0.0001520342 |
42041011305 | 0.375324 | 0.0001316705 |
42041011400 | 0.165817 | 0.0001124759 |
42041011500 | 0.130793 | 0.0001262873 |
42041011601 | 0.100112 | 0.0002310963 |
42041011602 | 0.292153 | 0.0001074462 |
42041011605 | 0.164799 | 0.0001331930 |
42041011700 | 0.277962 | 0.0001663621 |
42041011801 | 0.207928 | 0.0002363707 |
42041011802 | 0.217569 | 0.0002309331 |
42041011803 | 0.148192 | 0.0001942840 |
42041011901 | 0.215994 | 0.0001386578 |
42041011902 | 0.089888 | 0.0001669603 |
42041012000 | 0.072512 | 0.0001153850 |
42041012100 | 0.087161 | 0.0000557078 |
42041012200 | 0.020741 | 0.0000631573 |
42041012300 | 0.025892 | 0.0000646254 |
42041012400 | 0.145932 | 0.0001983350 |
42041012501 | 0.283421 | 0.0001154122 |
42041012502 | 0.258322 | 0.0001942568 |
42041012600 | 0.160706 | 0.0001531217 |
42041012701 | 0.262017 | 0.0001443672 |
42041012800 | 0.290434 | 0.0002161430 |
42041981001 | 0.172698 | 0.0001029874 |
42041981606 | 0.095376 | 0.0000569312 |
42043020100 | 0.165353 | 0.0000862397 |
42043020300 | 0.246603 | 0.0000495362 |
42043020400 | 0.006049 | 0.0000442345 |
42043020500 | 0.107982 | 0.0000728633 |
42043020600 | 0.313812 | 0.0000293628 |
42043020700 | 1.042475 | 0.0000747121 |
42043020800 | 0.412183 | 0.0000676704 |
42043020900 | 0.383379 | 0.0001010027 |
42043021100 | 0.775734 | 0.0000791165 |
42043021200 | 0.943307 | 0.0000628582 |
42043021300 | 0.700308 | 0.0001530673 |
42043021400 | 0.703712 | 0.0001331930 |
42043021500 | 0.657039 | 0.0001037486 |
42043021600 | 0.906943 | 0.0000826781 |
42043021700 | 0.457853 | 0.0001603808 |
42043021800 | 0.083122 | 0.0000538862 |
42043021901 | 0.081513 | 0.0001195719 |
42043021903 | 0.175657 | 0.0000940698 |
42043021904 | 0.017446 | 0.0001409143 |
42043022000 | 0.235022 | 0.0001410231 |
42043022100 | 0.054887 | 0.0001037758 |
42043022200 | 0.226924 | 0.0000780290 |
42043022300 | 0.125746 | 0.0001448294 |
42043022401 | 0.159715 | 0.0001089687 |
42043022403 | 0.015305 | 0.0001658999 |
42043022501 | 0.087075 | 0.0001544539 |
42043022502 | 0.054011 | 0.0001441225 |
42043022601 | 0.032323 | 0.0001877045 |
42043022604 | 0.122131 | 0.0001779441 |
42043022605 | 0.104614 | 0.0001240579 |
42043022606 | 0.251489 | 0.0000835481 |
42043022701 | 0.237481 | 0.0001075005 |
42043022702 | 0.011517 | 0.0001301208 |
42043022800 | 0.010239 | 0.0001466782 |
42043022900 | 0.071467 | 0.0002189705 |
42043023000 | 0.060466 | 0.0000445064 |
42043023100 | 0.026501 | 0.0000462193 |
42043023300 | 0.363871 | 0.0001186747 |
42043023400 | 0.073257 | 0.0000368123 |
42043023500 | 0.018388 | 0.0000655226 |
42043023601 | 0.138185 | 0.0000766424 |
42043023602 | 0.085338 | 0.0001552967 |
42043023700 | 0.052343 | 0.0000433917 |
42043023800 | 0.028128 | 0.0001160919 |
42043023900 | 0.144237 | 0.0000841734 |
42043024001 | 0.204060 | 0.0003493632 |
42043024002 | 0.182318 | 0.0001654106 |
42043024101 | 0.129150 | 0.0000546475 |
42043024102 | 0.177252 | 0.0001434428 |
42043024104 | 0.169744 | 0.0001645134 |
42043024105 | 0.156855 | 0.0001471132 |
42043024200 | 0.096455 | 0.0000676432 |
42043024300 | 0.165829 | 0.0000924385 |
42043024400 | 0.256657 | 0.0001252270 |
42043024502 | 0.261441 | 0.0001609789 |
42043024503 | 0.144809 | 0.0001801463 |
42043024600 | 0.168465 | 0.0002763911 |
42043024700 | 0.290675 | 0.0001656824 |
42045400301 | 0.894859 | 0.0001654106 |
42045400302 | 0.802033 | 0.0000996705 |
42045400401 | 0.903376 | 0.0001439322 |
42045400402 | 0.794907 | 0.0001296314 |
42045400500 | 0.634566 | 0.0001056246 |
42045400600 | 0.164899 | 0.0001343077 |
42045400700 | 0.372781 | 0.0001568192 |
42045400801 | 1.125384 | 0.0000611725 |
42045400802 | 0.052547 | 0.0000877622 |
42045400900 | 0.118369 | 0.0000405370 |
42045401000 | 0.073094 | 0.0000498352 |
42045401101 | 0.086618 | 0.0000742771 |
42045401103 | 0.083582 | 0.0000943960 |
42045401104 | 0.048359 | 0.0001062771 |
42045401200 | 0.139310 | 0.0000890672 |
42045401301 | 0.192720 | 0.0000652507 |
42045401302 | 0.049633 | 0.0000699814 |
42045401401 | 0.053134 | 0.0000556806 |
42045401402 | 0.019979 | 0.0000966526 |
42045401501 | 0.078455 | 0.0000928463 |
42045401502 | 0.149921 | 0.0001098659 |
42045401600 | 0.286768 | 0.0000470077 |
42045401700 | 0.588942 | 0.0000692201 |
42045401800 | 0.570057 | 0.0001104368 |
42045401900 | 0.215346 | 0.0001108718 |
42045402000 | 0.267246 | 0.0000594597 |
42045402100 | 1.457023 | 0.0001528498 |
42045402200 | 1.042070 | 0.0000614716 |
42045402300 | 1.546550 | 0.0000874088 |
42045402400 | 1.199928 | 0.0000820256 |
42045402500 | 1.238757 | 0.0001012202 |
42045402600 | 0.851385 | 0.0001060596 |
42045402700 | 1.139722 | 0.0000687036 |
42045402800 | 0.783494 | 0.0001515176 |
42045402900 | 1.327704 | 0.0000942057 |
42045403001 | 0.293923 | 0.0000818625 |
42045403002 | 0.140373 | 0.0000721836 |
42045403101 | 0.264308 | 0.0000951029 |
42045403103 | 0.345513 | 0.0000700630 |
42045403104 | 0.752308 | 0.0000644895 |
42045403200 | 0.100807 | 0.0001098115 |
42045403300 | 0.098430 | 0.0001792763 |
42045403401 | 0.181136 | 0.0000790621 |
42045403402 | 0.085123 | 0.0000967070 |
42045403501 | 0.102507 | 0.0001123672 |
42045403502 | 0.120145 | 0.0000771318 |
42045403601 | 0.173731 | 0.0001057877 |
42045403602 | 0.299446 | 0.0000481768 |
42045403701 | 0.207172 | 0.0000415158 |
42045403702 | 0.300197 | 0.0000678607 |
42045403800 | 0.179145 | 0.0001715550 |
42045403901 | 0.137875 | 0.0000925473 |
42045403902 | 0.215175 | 0.0000976858 |
42045404003 | 0.198911 | 0.0000604385 |
42045404004 | 0.279143 | 0.0001682925 |
42045404101 | 0.105908 | 0.0001727784 |
42045404102 | 0.060203 | 0.0001412950 |
42045404103 | 0.205761 | 0.0000995617 |
42045404300 | 0.017038 | 0.0000620969 |
42045404400 | 0.451500 | 0.0000464368 |
42045404500 | 0.713754 | 0.0001446935 |
42045404600 | 0.960913 | 0.0000508956 |
42045404700 | 0.088303 | 0.0001049177 |
42045404800 | 1.019074 | 0.0000546747 |
42045404900 | 1.432777 | 0.0000309125 |
42045405000 | 1.232356 | 0.0000478505 |
42045405100 | 1.307426 | 0.0000557078 |
42045405200 | 1.614774 | 0.0000750927 |
42045405300 | 0.955372 | 0.0000756636 |
42045405400 | 1.014139 | 0.0000625047 |
42045406100 | 0.042565 | 0.0000590519 |
42045406201 | 0.167176 | 0.0000868922 |
42045406202 | 0.163998 | 0.0001267767 |
42045406300 | 0.157124 | 0.0000833034 |
42045406401 | 1.187284 | 0.0000759355 |
42045406402 | 1.196205 | 0.0000317010 |
42045406500 | 0.112858 | 0.0000480680 |
42045406600 | 0.047688 | 0.0000605200 |
42045406700 | 0.077251 | 0.0000924929 |
42045406801 | 0.100618 | 0.0001085337 |
42045406802 | 0.090419 | 0.0001139712 |
42045406803 | 0.086700 | 0.0002294922 |
42045406902 | 0.205126 | 0.0001685372 |
42045406903 | 0.212917 | 0.0001323774 |
42045406904 | 0.114568 | 0.0001458082 |
42045407000 | 0.136064 | 0.0000712592 |
42045407101 | 0.125317 | 0.0001182125 |
42045407102 | 0.196692 | 0.0000894479 |
42045407201 | 0.228056 | 0.0001235142 |
42045407202 | 0.266720 | 0.0000987189 |
42045407401 | 0.081461 | 0.0000996433 |
42045407404 | 0.201132 | 0.0000769958 |
42045407501 | 0.178800 | 0.0000657401 |
42045407502 | 0.091826 | 0.0000796874 |
42045407600 | 0.108275 | 0.0001633443 |
42045407700 | 0.071827 | 0.0000713952 |
42045407801 | 0.211655 | 0.0001252270 |
42045407802 | 0.304492 | 0.0001665524 |
42045407803 | 0.274519 | 0.0001423825 |
42045407804 | 0.248054 | 0.0001188922 |
42045407805 | 0.244188 | 0.0000500527 |
42045407806 | 0.107949 | 0.0000434733 |
42045407901 | 0.216940 | 0.0001023349 |
42045407902 | 0.187922 | 0.0000735702 |
42045407903 | 0.175267 | 0.0000957010 |
42045408001 | 0.322453 | 0.0001598914 |
42045408002 | 0.193814 | 0.0001067937 |
42045408101 | 0.184933 | 0.0001488532 |
42045408102 | 0.210862 | 0.0000943688 |
42045408103 | 0.183343 | 0.0001204419 |
42045408300 | 0.061250 | 0.0001147053 |
42045408400 | 0.262792 | 0.0000570944 |
42045408500 | 0.107771 | 0.0001119593 |
42045408600 | 0.255231 | 0.0000901819 |
42045408700 | 0.199042 | 0.0001299305 |
42045408800 | 0.108995 | 0.0001288702 |
42045408900 | 0.324836 | 0.0000768871 |
42045409000 | 0.099190 | 0.0000964351 |
42045409100 | 0.236400 | 0.0001139441 |
42045409200 | 0.217674 | 0.0001122040 |
42045409300 | 0.192349 | 0.0000653323 |
42045409400 | 0.199105 | 0.0000794699 |
42045409500 | 0.145552 | 0.0001269398 |
42045409601 | 0.182066 | 0.0001164997 |
42045409602 | 0.090495 | 0.0001319968 |
42045409701 | 0.145541 | 0.0001813970 |
42045409702 | 0.106127 | 0.0000521462 |
42045409802 | 0.071061 | 0.0001570639 |
42045409803 | 0.064454 | 0.0001934412 |
42045409902 | 0.221991 | 0.0001432797 |
42045409903 | 0.172834 | 0.0001032049 |
42045409904 | 0.254258 | 0.0001102465 |
42045410000 | 0.214356 | 0.0001070112 |
42045410100 | 0.111813 | 0.0002055126 |
42045410200 | 0.182472 | 0.0000973867 |
42045410301 | 0.035567 | 0.0002144302 |
42045410302 | 0.289878 | 0.0002527921 |
42045410400 | 0.219457 | 0.0002463758 |
42045410500 | 1.644992 | 0.0001380868 |
42045410601 | 0.231005 | 0.0000985558 |
42045410602 | 0.142004 | 0.0001211760 |
42045410700 | 0.881237 | 0.0001463247 |
42045410800 | 0.162031 | 0.0002093188 |
42049000100 | 0.144472 | 0.0000361870 |
42049000200 | 0.180647 | 0.0001034224 |
42049000300 | 0.049587 | 0.0000887138 |
42049000400 | 0.067260 | 0.0000557894 |
42049000500 | 0.067414 | 0.0000894750 |
42049000600 | 0.053454 | 0.0000830587 |
42049000700 | 0.165654 | 0.0000569584 |
42049000800 | 0.148807 | 0.0000525268 |
42049000900 | 0.026981 | 0.0001281905 |
42049001000 | 0.033952 | 0.0000809924 |
42049001100 | 0.166154 | 0.0000674257 |
42049001200 | 0.161316 | 0.0000542668 |
42049001300 | 0.355154 | 0.0000475515 |
42049001400 | 0.036263 | 0.0000599219 |
42049001500 | 0.325300 | 0.0000776212 |
42049001600 | 0.039746 | 0.0001142431 |
42049001700 | 0.174835 | 0.0000663654 |
42049001800 | 0.369107 | 0.0000494274 |
42049001900 | 0.041513 | 0.0000467358 |
42049002000 | 0.091086 | 0.0000900732 |
42049002100 | 0.235089 | 0.0001007036 |
42049002200 | 0.220448 | 0.0001060868 |
42049002300 | 0.081005 | 0.0000713952 |
42049002400 | 0.118231 | 0.0000843365 |
42049002500 | 0.105521 | 0.0000585081 |
42049002600 | 0.019321 | 0.0000991811 |
42049002700 | 0.032576 | 0.0001835992 |
42049002800 | 0.176048 | 0.0001762313 |
42049002900 | 0.264921 | 0.0000779474 |
42049003000 | 0.070408 | 0.0001123400 |
42049010201 | 0.189732 | 0.0001592389 |
42049010202 | 0.306712 | 0.0001414581 |
42049010301 | 0.326121 | 0.0001274020 |
42049010303 | 0.281932 | 0.0001530401 |
42049010304 | 0.282248 | 0.0001153850 |
42049010400 | 0.309244 | 0.0001259067 |
42049010500 | 0.201719 | 0.0000926832 |
42049010700 | 0.150630 | 0.0001084249 |
42049010800 | 0.263836 | 0.0000943145 |
42049010902 | 0.260870 | 0.0001154938 |
42049010903 | 0.207125 | 0.0001694887 |
42049010904 | 0.244132 | 0.0001413494 |
42049011001 | 0.155980 | 0.0001673681 |
42049011002 | 0.165638 | 0.0001262601 |
42049011101 | 0.255216 | 0.0001448294 |
42049011102 | 0.256271 | 0.0000817809 |
42049011201 | 0.298724 | 0.0001215566 |
42049011202 | 0.303384 | 0.0001872152 |
42049011300 | 0.190067 | 0.0000834122 |
42049011400 | 0.222333 | 0.0001026067 |
42049011503 | 0.242910 | 0.0001047002 |
42049011505 | 0.267766 | 0.0000697911 |
42049011507 | 0.303635 | 0.0000874360 |
42049012300 | 0.250869 | 0.0002026306 |
42049012400 | 0.197898 | 0.0000393679 |
42051260300 | 0.318362 | 0.0000996161 |
42051260401 | 0.374206 | 0.0000608191 |
42055011700 | 0.283377 | 0.0002271269 |
42055011800 | 0.189088 | 0.0001039661 |
42055011900 | 0.172975 | 0.0001874055 |
42069100200 | 0.065150 | 0.0000708242 |
42069100300 | 0.064926 | 0.0001105456 |
42069100400 | 0.042601 | 0.0000561972 |
42069100500 | 0.099738 | 0.0000554087 |
42069100600 | 0.167775 | 0.0001110621 |
42069100800 | 0.045202 | 0.0000803943 |
42069100900 | 0.082677 | 0.0000448327 |
42069101000 | 0.159323 | 0.0000814546 |
42069101100 | 0.091039 | 0.0000779202 |
42069101200 | 0.158768 | 0.0000856416 |
42069101300 | 0.312994 | 0.0000806390 |
42069101400 | 0.308719 | 0.0000762890 |
42069101600 | 0.049554 | 0.0000644079 |
42069101700 | 0.247639 | 0.0000755277 |
42069101800 | 0.221713 | 0.0001193544 |
42069101900 | 0.152170 | 0.0000365132 |
42069102000 | 0.131705 | 0.0000613900 |
42069102100 | 0.222905 | 0.0000627222 |
42069102200 | 0.221844 | 0.0000609279 |
42069102300 | 0.070264 | 0.0000957826 |
42069102500 | 0.182701 | 0.0000781377 |
42069102600 | 0.231094 | 0.0000753374 |
42069102700 | 0.113985 | 0.0000722652 |
42069102800 | 0.207538 | 0.0000861853 |
42069102900 | 0.116257 | 0.0001105456 |
42069103000 | 0.066112 | 0.0000501887 |
42069103100 | 0.229250 | 0.0000445064 |
42069110100 | 0.287394 | 0.0000690298 |
42069110201 | 0.320037 | 0.0001116603 |
42069110202 | 0.287243 | 0.0001300392 |
42069110300 | 0.223143 | 0.0001044827 |
42069110401 | 0.226322 | 0.0001721259 |
42069110402 | 0.304252 | 0.0000706339 |
42069110403 | 0.123498 | 0.0000847715 |
42069110500 | 0.271528 | 0.0001337640 |
42069110600 | 0.290362 | 0.0000747664 |
42069110700 | 0.239666 | 0.0000679967 |
42069110800 | 0.223103 | 0.0000773221 |
42069110900 | 0.180053 | 0.0000758540 |
42069111000 | 0.240654 | 0.0000562787 |
42069111100 | 0.204926 | 0.0001884658 |
42069111200 | 0.355598 | 0.0001701412 |
42069111300 | 0.286724 | 0.0001207410 |
42069111400 | 0.179834 | 0.0001361293 |
42069111500 | 0.262581 | 0.0000857775 |
42069111600 | 0.196461 | 0.0000676161 |
42069111700 | 0.218269 | 0.0001035583 |
42069111800 | 0.299751 | 0.0002313953 |
42069112000 | 0.145007 | 0.0001135906 |
42069112100 | 0.314609 | 0.0001082074 |
42069112200 | 0.271166 | 0.0000624776 |
42069112300 | 0.143863 | 0.0000704164 |
42069112400 | 0.270834 | 0.0001186747 |
42069112500 | 0.198368 | 0.0001604624 |
42069112600 | 0.212012 | 0.0001348787 |
42069112700 | 0.278578 | 0.0000802040 |
42069112800 | 0.155126 | 0.0001566561 |
42069112901 | 0.219486 | 0.0001082890 |
42071000100 | 0.159714 | 0.0000713680 |
42071000200 | 0.460016 | 0.0000908616 |
42071000300 | 0.176074 | 0.0001268854 |
42071000400 | 0.127945 | 0.0001033408 |
42071000500 | 0.068767 | 0.0001259067 |
42071000600 | 0.113344 | 0.0000857231 |
42071000700 | 0.172247 | 0.0000888225 |
42071000800 | 0.757580 | 0.0000918132 |
42071000900 | 0.939919 | 0.0000938795 |
42071001000 | 0.604702 | 0.0000966798 |
42071001100 | 0.267327 | 0.0000864028 |
42071001200 | 0.390923 | 0.0001472763 |
42071001400 | 0.714848 | 0.0001278642 |
42071010101 | 0.317025 | 0.0001950181 |
42071010102 | 0.165297 | 0.0001023621 |
42071010201 | 0.332648 | 0.0001290061 |
42071010202 | 0.282282 | 0.0001619577 |
42071010300 | 0.211825 | 0.0002562178 |
42071010400 | 0.226038 | 0.0001290877 |
42071010501 | 0.358748 | 0.0001221820 |
42071010502 | 0.260673 | 0.0002023588 |
42071010600 | 0.160147 | 0.0002943895 |
42071010701 | 0.154780 | 0.0001508379 |
42071010702 | 0.118226 | 0.0001587767 |
42071010801 | 0.249490 | 0.0002396332 |
42071010802 | 0.230803 | 0.0000932270 |
42071010900 | 0.098902 | 0.0002159255 |
42071011000 | 0.205922 | 0.0000696551 |
42071011100 | 0.245410 | 0.0002203843 |
42071011200 | 0.101746 | 0.0000539406 |
42071011300 | 0.047290 | 0.0001120409 |
42071011400 | 0.069248 | 0.0001073918 |
42071011502 | 0.164914 | 0.0001654106 |
42071011503 | 0.139111 | 0.0001428991 |
42071011504 | 0.125053 | 0.0002064098 |
42071011600 | 0.128423 | 0.0001685100 |
42071011701 | 0.181237 | 0.0001198710 |
42071011703 | 0.237148 | 0.0002125270 |
42071011704 | 0.135960 | 0.0001203332 |
42071011705 | 0.047355 | 0.0001470588 |
42071011801 | 0.138846 | 0.0000773221 |
42071011802 | 0.138001 | 0.0001591845 |
42071011803 | 0.043999 | 0.0001743825 |
42071011804 | 0.062877 | 0.0002244624 |
42071011805 | 0.157733 | 0.0000682414 |
42071011901 | 0.133616 | 0.0001605711 |
42071011902 | 0.184096 | 0.0002027394 |
42071012001 | 0.191128 | 0.0001440953 |
42071012002 | 0.235662 | 0.0001079356 |
42071012102 | 0.206006 | 0.0002258762 |
42071012103 | 0.143492 | 0.0001204963 |
42071012104 | 0.231342 | 0.0001607614 |
42071012200 | 0.154827 | 0.0001956162 |
42071012301 | 0.153270 | 0.0000871641 |
42071012302 | 0.146622 | 0.0000857775 |
42071012402 | 0.182032 | 0.0001086696 |
42071012403 | 0.171259 | 0.0001250095 |
42071012404 | 0.263530 | 0.0001524692 |
42071012501 | 0.151675 | 0.0002327819 |
42071012502 | 0.209896 | 0.0001157928 |
42071012601 | 0.290996 | 0.0002042347 |
42071012602 | 0.307857 | 0.0001314530 |
42071012700 | 0.246283 | 0.0002166324 |
42071012800 | 0.145045 | 0.0001397996 |
42071012900 | 0.281780 | 0.0001953715 |
42071013000 | 0.165368 | 0.0002259578 |
42071013101 | 0.087814 | 0.0001378965 |
42071013102 | 0.178557 | 0.0000995345 |
42071013202 | 0.034223 | 0.0001527139 |
42071013203 | 0.089715 | 0.0001435788 |
42071013204 | 0.087804 | 0.0001871336 |
42071013301 | 0.140276 | 0.0001176144 |
42071013303 | 0.237827 | 0.0001266408 |
42071013304 | 0.249452 | 0.0002146748 |
42071013400 | 0.104108 | 0.0000839287 |
42071013501 | 0.236582 | 0.0002710895 |
42071013502 | 0.067478 | 0.0001200069 |
42071013503 | 0.238857 | 0.0000626951 |
42071013601 | 0.062232 | 0.0000601938 |
42071013602 | 0.100871 | 0.0001682925 |
42071013701 | 0.086513 | 0.0001301208 |
42071013702 | 0.047836 | 0.0002612203 |
42071013800 | 0.295131 | 0.0001049449 |
42071013901 | 0.246927 | 0.0001346340 |
42071013902 | 0.282136 | 0.0001034224 |
42071014000 | 0.238621 | 0.0001967309 |
42071014101 | 0.196435 | 0.0001522788 |
42071014102 | 0.200644 | 0.0001523332 |
42071014201 | 0.263250 | 0.0001495057 |
42071014202 | 0.208614 | 0.0003121703 |
42071014300 | 0.260200 | 0.0002085576 |
42071014401 | 0.217125 | 0.0001889552 |
42071014501 | 0.308543 | 0.0001415125 |
42071014700 | 1.216497 | 0.0001229432 |
42073010500 | 0.374206 | 0.0000787359 |
42075002300 | 0.155075 | 0.0000787087 |
42075002400 | 0.294319 | 0.0000671539 |
42075003000 | 0.272819 | 0.0003106478 |
42075003700 | 0.252374 | 0.0000809381 |
42075003800 | 0.216882 | 0.0002259034 |
42075003901 | 0.142590 | 0.0000964623 |
42075003902 | 0.141681 | 0.0001060324 |
42075004000 | 0.283953 | 0.0002222330 |
42077000101 | 0.298193 | 0.0001048633 |
42077000102 | 0.465331 | 0.0001104368 |
42077000400 | 0.584685 | 0.0001153306 |
42077000500 | 1.177489 | 0.0000699270 |
42077000600 | 0.828793 | 0.0001687547 |
42077000700 | 1.144220 | 0.0001002142 |
42077000800 | 1.162930 | 0.0001124215 |
42077000900 | 1.248162 | 0.0000419780 |
42077001000 | 0.969805 | 0.0000890400 |
42077001200 | 0.847450 | 0.0000735974 |
42077001401 | 0.689300 | 0.0002103248 |
42077001402 | 0.145822 | 0.0000516840 |
42077001501 | 0.790466 | 0.0001705762 |
42077001502 | 0.361153 | 0.0001840070 |
42077001600 | 1.036617 | 0.0001000239 |
42077001700 | 1.369811 | 0.0001382228 |
42077001800 | 1.037696 | 0.0001204419 |
42077001900 | 0.529711 | 0.0001098659 |
42077002000 | 0.822605 | 0.0001505388 |
42077002100 | 0.582904 | 0.0001913749 |
42077002201 | 0.133979 | 0.0001155481 |
42077002202 | 0.059502 | 0.0001343077 |
42077002301 | 0.111419 | 0.0001813426 |
42077002302 | 0.016747 | 0.0000763705 |
42077005100 | 0.244067 | 0.0001130469 |
42077005200 | 0.340532 | 0.0001807173 |
42077005301 | 0.217731 | 0.0000943688 |
42077005401 | 0.229670 | 0.0000593781 |
42077005402 | 0.245434 | 0.0001393646 |
42077005503 | 0.277319 | 0.0001213935 |
42077005504 | 0.210662 | 0.0001210944 |
42077005505 | 0.189012 | 0.0000923841 |
42077005506 | 0.145503 | 0.0000998064 |
42077005601 | 0.103427 | 0.0001306646 |
42077005602 | 0.157194 | 0.0001203604 |
42077005702 | 0.139156 | 0.0001070927 |
42077005703 | 0.228083 | 0.0000994801 |
42077005704 | 0.184522 | 0.0000990723 |
42077005705 | 0.061811 | 0.0001709569 |
42077005800 | 0.078227 | 0.0000856959 |
42077005901 | 0.107690 | 0.0001771829 |
42077005902 | 0.089155 | 0.0000442617 |
42077006001 | 0.144523 | 0.0001231607 |
42077006002 | 0.135772 | 0.0001475754 |
42077006101 | 0.090503 | 0.0001018183 |
42077006102 | 0.110352 | 0.0001546714 |
42077006202 | 0.075808 | 0.0003142637 |
42077006203 | 0.214916 | 0.0002200580 |
42077006204 | 0.123356 | 0.0001038574 |
42077006302 | 0.063215 | 0.0001971659 |
42077006303 | 0.146819 | 0.0000836297 |
42077006304 | 0.103567 | 0.0001039118 |
42077006305 | 0.082570 | 0.0001834904 |
42077006307 | 0.095998 | 0.0002352016 |
42077006308 | 0.061032 | 0.0002046425 |
42077006401 | 0.182559 | 0.0000833034 |
42077006402 | 0.270444 | 0.0001352049 |
42077006500 | 0.064885 | 0.0001524692 |
42077006600 | 0.224011 | 0.0001415669 |
42077006701 | 0.130717 | 0.0001350146 |
42077006702 | 0.179059 | 0.0000779202 |
42077006703 | 0.200139 | 0.0001545898 |
42077006800 | 0.170810 | 0.0001250911 |
42077006902 | 0.138531 | 0.0000662023 |
42077006903 | 0.184880 | 0.0001864267 |
42077006905 | 0.165086 | 0.0001428447 |
42077006906 | 0.174659 | 0.0001081259 |
42077007000 | 0.268472 | 0.0002120648 |
42077009100 | 0.063111 | 0.0000961632 |
42077009200 | 0.060913 | 0.0001026611 |
42077009300 | 0.141169 | 0.0000881156 |
42077009400 | 0.203974 | 0.0001154938 |
42077009500 | 0.320584 | 0.0001245745 |
42077009600 | 0.760486 | 0.0002143758 |
42077009700 | 0.761442 | 0.0000834665 |
42079200100 | 0.054970 | 0.0000792252 |
42079200200 | 0.001652 | 0.0000811012 |
42079200300 | 0.051470 | 0.0000445064 |
42079200400 | 0.119968 | 0.0000673442 |
42079200500 | 0.129216 | 0.0000681870 |
42079200600 | 0.032693 | 0.0000598947 |
42079200700 | 0.048294 | 0.0000935532 |
42079200800 | 0.325202 | 0.0001079356 |
42079200900 | 0.116150 | 0.0000762346 |
42079201000 | 0.140594 | 0.0000532065 |
42079201100 | 0.356199 | 0.0000371929 |
42079201200 | 0.057679 | 0.0000479321 |
42079201300 | 0.131956 | 0.0000526356 |
42079201400 | 0.137827 | 0.0000589431 |
42079201500 | 0.094281 | 0.0000663382 |
42079201600 | 0.074398 | 0.0000717214 |
42079210100 | 0.321039 | 0.0000901004 |
42079210200 | 0.239301 | 0.0000715583 |
42079210300 | 0.343553 | 0.0000710689 |
42079210400 | 0.309257 | 0.0000384707 |
42079210500 | 0.233200 | 0.0001294955 |
42079210600 | 0.199372 | 0.0000274869 |
42079210700 | 0.055829 | 0.0000482312 |
42079210800 | 0.170760 | 0.0000854784 |
42079210900 | 0.177099 | 0.0000438811 |
42079211000 | 0.173612 | 0.0001281905 |
42079211101 | 0.242433 | 0.0001497232 |
42079211102 | 0.297000 | 0.0000581547 |
42079211201 | 0.249322 | 0.0000753918 |
42079211204 | 0.243162 | 0.0001675312 |
42079211205 | 0.329157 | 0.0000794971 |
42079211301 | 0.044540 | 0.0001254717 |
42079211302 | 0.297671 | 0.0000951573 |
42079211303 | 0.304146 | 0.0000750927 |
42079211304 | 0.274374 | 0.0000636466 |
42079211400 | 0.266867 | 0.0001874870 |
42079211500 | 0.229444 | 0.0000727817 |
42079211600 | 0.298994 | 0.0000815090 |
42079211701 | 0.222172 | 0.0001432253 |
42079211702 | 0.296131 | 0.0000410808 |
42079211800 | 0.115245 | 0.0000532609 |
42079211900 | 0.148714 | 0.0001580427 |
42079212000 | 0.210337 | 0.0000458386 |
42079212100 | 0.230971 | 0.0001103281 |
42079212200 | 0.295403 | 0.0001364012 |
42079212300 | 0.277360 | 0.0000765880 |
42079212700 | 0.140578 | 0.0001302024 |
42079212800 | 0.228711 | 0.0000868922 |
42079212900 | 0.278388 | 0.0000383348 |
42079213000 | 0.149561 | 0.0000364316 |
42079213100 | 0.101898 | 0.0000496721 |
42079213200 | 0.030896 | 0.0001259882 |
42079213300 | 0.185639 | 0.0000415973 |
42079213400 | 0.178060 | 0.0001179407 |
42079213600 | 0.225203 | 0.0000537231 |
42079213700 | 0.072808 | 0.0000547018 |
42079213800 | 0.178424 | 0.0000446424 |
42079213900 | 0.307320 | 0.0000437180 |
42079214000 | 0.127125 | 0.0000320000 |
42079214100 | 0.202293 | 0.0000607647 |
42079214200 | 0.143991 | 0.0000775124 |
42079214300 | 0.308678 | 0.0000521734 |
42079214400 | 0.153977 | 0.0000510587 |
42079214500 | 0.334450 | 0.0000404826 |
42079214600 | 0.212683 | 0.0000989364 |
42079214900 | 0.315965 | 0.0000345829 |
42079215000 | 0.224436 | 0.0000440442 |
42079215100 | 0.181170 | 0.0000730808 |
42079215200 | 0.148093 | 0.0000742499 |
42079215300 | 0.230284 | 0.0001052711 |
42079215501 | 0.207631 | 0.0001193544 |
42079215502 | 0.265976 | 0.0001514632 |
42079215503 | 0.283313 | 0.0000941513 |
42079215504 | 0.348223 | 0.0001067665 |
42079215600 | 0.057332 | 0.0001428175 |
42079218000 | 0.089131 | 0.0001164997 |
42085030100 | 0.151359 | 0.0000499712 |
42085030300 | 0.082731 | 0.0000905897 |
42085030400 | 0.206884 | 0.0000715583 |
42085030500 | 0.138790 | 0.0000558437 |
42085030900 | 0.153322 | 0.0000734342 |
42085031100 | 0.167474 | 0.0000399389 |
42085031200 | 0.200582 | 0.0001465966 |
42085031300 | 0.260330 | 0.0000699814 |
42085031400 | 0.133348 | 0.0001363468 |
42085031700 | 0.298992 | 0.0000653595 |
42085032300 | 0.289109 | 0.0000835753 |
42085032701 | 0.292634 | 0.0001222907 |
42085033200 | 0.131021 | 0.0000738421 |
42085033300 | 0.295024 | 0.0000742499 |
42085033400 | 0.325338 | 0.0000655770 |
42089301101 | 0.064097 | 0.0001521701 |
42089301102 | 0.102234 | 0.0000809109 |
42089301203 | 0.169340 | 0.0001562483 |
42091200103 | 0.179225 | 0.0001078812 |
42091200104 | 0.280784 | 0.0001178591 |
42091200105 | 0.223665 | 0.0000743858 |
42091200106 | 0.292921 | 0.0000529346 |
42091200200 | 0.241381 | 0.0000363229 |
42091200301 | 0.067426 | 0.0001712559 |
42091200305 | 0.216862 | 0.0000568225 |
42091200306 | 0.289291 | 0.0000927919 |
42091200307 | 0.028004 | 0.0000711233 |
42091200308 | 0.068273 | 0.0001029602 |
42091200309 | 0.167741 | 0.0000689211 |
42091200310 | 0.287867 | 0.0000663926 |
42091200401 | 0.083033 | 0.0000908344 |
42091200402 | 0.073430 | 0.0001081259 |
42091200501 | 0.168573 | 0.0001093493 |
42091200502 | 0.057049 | 0.0001382771 |
42091200505 | 0.158494 | 0.0001941209 |
42091200506 | 0.247635 | 0.0001227529 |
42091200507 | 0.116732 | 0.0001402890 |
42091200602 | 0.208475 | 0.0002134786 |
42091200603 | 0.091234 | 0.0000953204 |
42091200605 | 0.464001 | 0.0001823486 |
42091200606 | 0.179305 | 0.0000856687 |
42091200607 | 0.227748 | 0.0001162278 |
42091200703 | 0.200658 | 0.0001131828 |
42091200704 | 0.068625 | 0.0000860494 |
42091200707 | 0.158813 | 0.0001109262 |
42091200708 | 0.281242 | 0.0001547529 |
42091200800 | 0.281386 | 0.0000895566 |
42091200901 | 0.230687 | 0.0001088871 |
42091200902 | 0.273731 | 0.0000371385 |
42091200903 | 0.169403 | 0.0001206594 |
42091200906 | 0.170709 | 0.0000504606 |
42091200907 | 0.221514 | 0.0000673985 |
42091200908 | 0.038416 | 0.0000545931 |
42091201003 | 0.250105 | 0.0001287614 |
42091201004 | 0.248855 | 0.0001438234 |
42091201005 | 0.203179 | 0.0000936348 |
42091201006 | 0.150604 | 0.0000591606 |
42091201100 | 0.137826 | 0.0000862941 |
42091201201 | 0.262540 | 0.0001647852 |
42091201203 | 0.232250 | 0.0000833578 |
42091201204 | 0.075256 | 0.0000590791 |
42091201301 | 0.025335 | 0.0000918948 |
42091201302 | 0.002154 | 0.0000795515 |
42091201404 | 0.190304 | 0.0001393918 |
42091201406 | 0.121630 | 0.0001296586 |
42091201407 | 0.036347 | 0.0000712320 |
42091201408 | 0.242509 | 0.0001089687 |
42091201409 | 0.238085 | 0.0001175872 |
42091201410 | 0.180228 | 0.0000619882 |
42091201411 | 0.236539 | 0.0000722924 |
42091201501 | 0.156676 | 0.0000926832 |
42091201502 | 0.108380 | 0.0000525540 |
42091201603 | 0.107881 | 0.0001090231 |
42091201604 | 0.071592 | 0.0000777027 |
42091201605 | 0.050654 | 0.0000839831 |
42091201606 | 0.115130 | 0.0000616075 |
42091201607 | 0.094643 | 0.0000913782 |
42091201608 | 0.133005 | 0.0001218285 |
42091201703 | 0.077115 | 0.0000886594 |
42091201704 | 0.130317 | 0.0000886594 |
42091201705 | 0.196788 | 0.0001122856 |
42091201706 | 0.011094 | 0.0001313986 |
42091201800 | 0.065991 | 0.0000815362 |
42091201901 | 0.166432 | 0.0001300936 |
42091201902 | 0.060978 | 0.0001410503 |
42091202000 | 0.238268 | 0.0000681326 |
42091202100 | 0.038104 | 0.0001188650 |
42091202201 | 0.036337 | 0.0001316433 |
42091202202 | 0.496018 | 0.0000810740 |
42091202301 | 0.044129 | 0.0001148141 |
42091202302 | 0.144878 | 0.0000573119 |
42091202401 | 0.812315 | 0.0000971964 |
42091202402 | 0.316033 | 0.0001176960 |
42091202500 | 0.480097 | 0.0001439866 |
42091202602 | 0.087271 | 0.0000690570 |
42091202603 | 0.063141 | 0.0000921938 |
42091202604 | 0.015427 | 0.0000608463 |
42091203000 | 0.102111 | 0.0000806118 |
42091203103 | 0.176761 | 0.0000810740 |
42091203104 | 0.250022 | 0.0001161463 |
42091203105 | 0.155400 | 0.0001421378 |
42091203106 | 0.142148 | 0.0000604657 |
42091203203 | 0.153076 | 0.0001070384 |
42091203204 | 0.206545 | 0.0001869161 |
42091203205 | 0.100717 | 0.0000578556 |
42091203207 | 0.198853 | 0.0000871369 |
42091203208 | 0.219411 | 0.0000742499 |
42091203302 | 0.061250 | 0.0001712559 |
42091203303 | 0.028063 | 0.0001089687 |
42091203304 | 0.016076 | 0.0000948310 |
42091203401 | 0.014512 | 0.0001559492 |
42091203402 | 0.051822 | 0.0001740019 |
42091203403 | 0.056304 | 0.0000796874 |
42091203500 | 0.260333 | 0.0001659543 |
42091203601 | 0.700808 | 0.0000656585 |
42091203602 | 0.229632 | 0.0001037486 |
42091203700 | 0.156675 | 0.0000486390 |
42091203801 | 0.180587 | 0.0000973595 |
42091203803 | 0.486694 | 0.0001466238 |
42091203804 | 0.311460 | 0.0000838744 |
42091203901 | 0.882705 | 0.0000881700 |
42091203902 | 0.478437 | 0.0000921394 |
42091204002 | 0.016362 | 0.0000962720 |
42091204007 | 0.098067 | 0.0000571759 |
42091204008 | 0.121746 | 0.0000736246 |
42091204009 | 0.067460 | 0.0000557078 |
42091204010 | 0.164679 | 0.0000700086 |
42091204101 | 0.259429 | 0.0001024436 |
42091204102 | 0.148655 | 0.0001108990 |
42091204200 | 0.128401 | 0.0000368667 |
42091204300 | 0.156002 | 0.0000694648 |
42091204400 | 0.132172 | 0.0000883875 |
42091204500 | 0.108646 | 0.0001240307 |
42091204600 | 0.146021 | 0.0001247920 |
42091204701 | 0.250742 | 0.0000604385 |
42091204702 | 0.215793 | 0.0000808565 |
42091204800 | 0.228570 | 0.0001351505 |
42091204900 | 0.155163 | 0.0001422737 |
42091205000 | 0.093886 | 0.0000664198 |
42091205100 | 0.097406 | 0.0000439627 |
42091205200 | 0.251378 | 0.0000736246 |
42091205300 | 0.064101 | 0.0000510859 |
42091205400 | 0.225657 | 0.0001703587 |
42091205501 | 0.020062 | 0.0001008123 |
42091205502 | 0.183817 | 0.0000970876 |
42091205503 | 0.085606 | 0.0001339543 |
42091205600 | 0.071818 | 0.0001120953 |
42091205700 | 0.110059 | 0.0001212576 |
42091205801 | 0.734667 | 0.0000931998 |
42091205805 | 0.208207 | 0.0000822159 |
42091205806 | 0.139926 | 0.0000528803 |
42091205807 | 0.454563 | 0.0000478233 |
42091205808 | 0.234359 | 0.0001456178 |
42091205809 | 0.149316 | 0.0000813459 |
42091205903 | 0.159758 | 0.0000761258 |
42091205904 | 0.173987 | 0.0000651691 |
42091205905 | 0.382358 | 0.0001030689 |
42091205906 | 0.037637 | 0.0000546203 |
42091206004 | 0.046657 | 0.0001831642 |
42091206005 | 0.156070 | 0.0001192729 |
42091206006 | 0.127036 | 0.0000790893 |
42091206007 | 0.360092 | 0.0001838439 |
42091206102 | 0.194144 | 0.0002512696 |
42091206104 | 0.091469 | 0.0000895022 |
42091206105 | 0.282624 | 0.0001742466 |
42091206106 | 0.090857 | 0.0001247920 |
42091206201 | 0.215627 | 0.0000651148 |
42091206202 | 0.032871 | 0.0000601666 |
42091206300 | 0.081714 | 0.0001366731 |
42091206400 | 0.110311 | 0.0000972507 |
42091206501 | 0.202523 | 0.0001126390 |
42091206502 | 0.138742 | 0.0001299577 |
42091206600 | 0.170823 | 0.0000378998 |
42091206702 | 0.599934 | 0.0000899372 |
42091206703 | 0.241908 | 0.0001051624 |
42091206704 | 0.223389 | 0.0001950996 |
42091206801 | 0.172667 | 0.0002053494 |
42091206802 | 0.259489 | 0.0000734342 |
42091206901 | 0.181534 | 0.0001248735 |
42091206904 | 0.086133 | 0.0001636977 |
42091206905 | 0.216868 | 0.0001236229 |
42091206906 | 0.190985 | 0.0000786815 |
42091207001 | 0.113053 | 0.0002129620 |
42091207003 | 0.176026 | 0.0000820256 |
42091207004 | 0.149664 | 0.0001176960 |
42091207101 | 0.244858 | 0.0001633987 |
42091207103 | 0.217568 | 0.0001174785 |
42091207104 | 0.312377 | 0.0000763705 |
42091207201 | 0.125467 | 0.0000656042 |
42091207202 | 0.121509 | 0.0001219373 |
42091207300 | 0.101765 | 0.0000709058 |
42091207400 | 0.182246 | 0.0000793068 |
42091207500 | 0.338282 | 0.0000904810 |
42091207600 | 0.270724 | 0.0001027699 |
42091207800 | 0.145733 | 0.0002047785 |
42091207900 | 0.141807 | 0.0000662567 |
42091208000 | 0.193930 | 0.0001019270 |
42091208100 | 0.202617 | 0.0000778930 |
42091208201 | 0.318564 | 0.0000555719 |
42091208203 | 0.201047 | 0.0001350418 |
42091208204 | 0.285891 | 0.0000910519 |
42091208301 | 0.341297 | 0.0000694376 |
42091208302 | 0.178164 | 0.0002775602 |
42091208400 | 0.304447 | 0.0001952628 |
42091208500 | 0.165688 | 0.0001318608 |
42091208601 | 0.200752 | 0.0003440344 |
42091208603 | 0.169883 | 0.0003410981 |
42091208604 | 0.131486 | 0.0001597283 |
42091208702 | 0.112865 | 0.0000878710 |
42091208703 | 0.110954 | 0.0001060324 |
42091208704 | 0.060815 | 0.0002534446 |
42091208801 | 0.149872 | 0.0000364045 |
42091208802 | 0.039635 | 0.0000655498 |
42091208901 | 0.065464 | 0.0000940970 |
42091208903 | 0.143820 | 0.0000749839 |
42091208904 | 0.134430 | 0.0000835753 |
42091208905 | 0.059677 | 0.0000760443 |
42091208906 | 0.143099 | 0.0001103553 |
42091209000 | 0.072932 | 0.0000340663 |
42091209100 | 0.122218 | 0.0001478744 |
42091209201 | 0.090633 | 0.0000412439 |
42091209202 | 0.091746 | 0.0000597588 |
42091210100 | 0.073645 | 0.0001015192 |
42091210200 | 0.053445 | 0.0000753374 |
42091210300 | 0.109336 | 0.0001167988 |
42091210400 | 0.023037 | 0.0001179678 |
42091210500 | 0.058102 | 0.0001070384 |
42091210600 | 0.125294 | 0.0001150859 |
42091210700 | 0.149802 | 0.0001481463 |
42095010100 | 0.134889 | 0.0001031777 |
42095010200 | 0.117965 | 0.0000976858 |
42095010300 | 0.121031 | 0.0000882244 |
42095010400 | 0.073233 | 0.0001506748 |
42095010500 | 0.896914 | 0.0001131284 |
42095010600 | 0.155502 | 0.0002059476 |
42095010700 | 0.185846 | 0.0001191913 |
42095010800 | 0.110042 | 0.0000583994 |
42095010900 | 0.602973 | 0.0000948310 |
42095011000 | 0.217868 | 0.0000822431 |
42095011100 | 0.125173 | 0.0000922482 |
42095011200 | 0.689596 | 0.0001499951 |
42095011300 | 0.560056 | 0.0001206594 |
42095014100 | 0.046469 | 0.0001594021 |
42095014200 | 0.097087 | 0.0001439322 |
42095014300 | 0.169845 | 0.0001009483 |
42095014400 | 0.032630 | 0.0000569584 |
42095014500 | 0.218436 | 0.0000807749 |
42095014600 | 0.363716 | 0.0000874903 |
42095014700 | 0.087456 | 0.0000736517 |
42095015201 | 0.272477 | 0.0001940937 |
42095015300 | 0.184547 | 0.0001402075 |
42095015400 | 0.284100 | 0.0000830859 |
42095015500 | 0.305136 | 0.0001682381 |
42095015600 | 0.179770 | 0.0000958370 |
42095015700 | 0.239151 | 0.0000732439 |
42095015801 | 0.302927 | 0.0001444760 |
42095015802 | 0.288703 | 0.0000847987 |
42095015901 | 0.319446 | 0.0001507020 |
42095015902 | 0.293815 | 0.0001064674 |
42095016001 | 0.334313 | 0.0001577708 |
42095016002 | 0.290841 | 0.0001232151 |
42095016100 | 0.259047 | 0.0000551369 |
42095016201 | 0.114478 | 0.0001416212 |
42095016202 | 0.159099 | 0.0001175328 |
42095016300 | 0.176470 | 0.0000758540 |
42095016400 | 0.093468 | 0.0001301480 |
42095016500 | 0.222547 | 0.0001318880 |
42095016600 | 0.108336 | 0.0000704164 |
42095016700 | 0.183800 | 0.0001859645 |
42095016800 | 0.251186 | 0.0001490707 |
42095016901 | 0.210214 | 0.0000863756 |
42095016902 | 0.121308 | 0.0000825965 |
42095017000 | 0.162578 | 0.0000549465 |
42095017101 | 0.001573 | 0.0001678031 |
42095017102 | 0.037240 | 0.0002440648 |
42095017200 | 0.091500 | 0.0001577436 |
42095017300 | 0.077116 | 0.0000684317 |
42095017401 | 0.033929 | 0.0002151914 |
42095017402 | 0.142499 | 0.0001058149 |
42095017501 | 0.081953 | 0.0001066305 |
42095017502 | 0.091415 | 0.0001452100 |
42095017603 | 0.084645 | 0.0000982295 |
42095017604 | 0.046825 | 0.0001181310 |
42095017605 | 0.099648 | 0.0001123944 |
42095017606 | 0.039980 | 0.0001274564 |
42095017607 | 0.078622 | 0.0001730503 |
42095017702 | 0.152447 | 0.0000602482 |
42095017703 | 0.079030 | 0.0000772677 |
42095017704 | 0.127414 | 0.0001673137 |
42095017800 | 0.086788 | 0.0000699542 |
42095017901 | 0.120822 | 0.0000959185 |
42095017902 | 0.171277 | 0.0000609550 |
42095018001 | 0.236393 | 0.0001080987 |
42095018002 | 0.123833 | 0.0001800104 |
42095018100 | 0.107370 | 0.0001729144 |
42095018300 | 0.173328 | 0.0001283536 |
42099030301 | 0.263485 | 0.0001257979 |
42099030400 | 0.212009 | 0.0001299577 |
42101000100 | 0.053076 | 0.0001096484 |
42101000200 | 1.502427 | 0.0000755821 |
42101000300 | 0.161793 | 0.0000848803 |
42101000401 | 0.175375 | 0.0000665829 |
42101000402 | 0.138075 | 0.0001088599 |
42101000500 | 0.283406 | 0.0000609007 |
42101000600 | 0.054788 | 0.0000330875 |
42101000700 | 0.153460 | 0.0000983383 |
42101000801 | 0.175846 | 0.0000401292 |
42101000803 | 0.138959 | 0.0000720205 |
42101000804 | 0.177156 | 0.0001284623 |
42101000901 | 0.199319 | 0.0000544843 |
42101000902 | 0.156660 | 0.0000737605 |
42101001001 | 0.177667 | 0.0000711233 |
42101001002 | 0.135821 | 0.0000914326 |
42101001101 | 0.049090 | 0.0000982839 |
42101001102 | 0.145541 | 0.0000704164 |
42101001201 | 0.068580 | 0.0001017095 |
42101001202 | 0.084847 | 0.0001386578 |
42101001300 | 0.027356 | 0.0001799832 |
42101001400 | 0.075988 | 0.0001109262 |
42101001500 | 0.032564 | 0.0000863756 |
42101001600 | 0.101353 | 0.0000622329 |
42101001700 | 0.086560 | 0.0000796874 |
42101001800 | 0.056705 | 0.0000837928 |
42101001900 | 0.074491 | 0.0001089687 |
42101002000 | 0.523983 | 0.0000467086 |
42101002100 | 0.420972 | 0.0000587800 |
42101002200 | 0.177950 | 0.0000596500 |
42101002300 | 0.223809 | 0.0000780834 |
42101002400 | 0.087497 | 0.0001232695 |
42101002500 | 0.123091 | 0.0001093765 |
42101002701 | 0.269468 | 0.0001129381 |
42101002702 | 0.105290 | 0.0001173425 |
42101002801 | 0.694491 | 0.0001215295 |
42101002802 | 0.179707 | 0.0001508923 |
42101002900 | 0.153138 | 0.0001048361 |
42101003001 | 0.491106 | 0.0001045371 |
42101003002 | 0.486187 | 0.0000735974 |
42101003100 | 0.595855 | 0.0001133187 |
42101003200 | 0.985805 | 0.0001082074 |
42101003300 | 0.224060 | 0.0001662262 |
42101003600 | 0.795962 | 0.0001893630 |
42101003701 | 0.722273 | 0.0001555142 |
42101003702 | 0.677537 | 0.0001089415 |
42101003800 | 0.177399 | 0.0001087784 |
42101003901 | 0.168723 | 0.0001674496 |
42101003902 | 0.272191 | 0.0001551064 |
42101004001 | 0.113244 | 0.0001127750 |
42101004002 | 0.131541 | 0.0001259339 |
42101004101 | 0.723809 | 0.0001512729 |
42101004102 | 0.937618 | 0.0002242178 |
42101004201 | 0.242568 | 0.0001441497 |
42101004202 | 0.209179 | 0.0001481463 |
42101005400 | 0.892255 | 0.0000419508 |
42101005500 | 0.840481 | 0.0001693800 |
42101005600 | 1.502562 | 0.0000296619 |
42101006000 | 1.084542 | 0.0001643230 |
42101006100 | 1.160550 | 0.0000750111 |
42101006200 | 1.332892 | 0.0001357759 |
42101006300 | 1.241244 | 0.0001214207 |
42101006400 | 1.232271 | 0.0001189194 |
42101006500 | 1.712592 | 0.0001189466 |
42101006600 | 1.227584 | 0.0000936076 |
42101006700 | 1.276618 | 0.0001830282 |
42101006900 | 1.514209 | 0.0000945863 |
42101007000 | 1.653911 | 0.0000954020 |
42101007101 | 1.467804 | 0.0000705523 |
42101007102 | 1.437169 | 0.0001214479 |
42101007200 | 1.451950 | 0.0001168531 |
42101007300 | 1.124236 | 0.0000790621 |
42101007400 | 1.209426 | 0.0001190554 |
42101007700 | 0.210313 | 0.0000481768 |
42101007800 | 0.043141 | 0.0001083706 |
42101007900 | 0.087183 | 0.0001154666 |
42101008000 | 0.676647 | 0.0000998880 |
42101008101 | 1.594412 | 0.0000843909 |
42101008102 | 1.335146 | 0.0001451285 |
42101008200 | 1.549944 | 0.0001579883 |
42101008301 | 1.571124 | 0.0001235413 |
42101008302 | 1.606926 | 0.0001369177 |
42101008400 | 1.557749 | 0.0001333561 |
42101008500 | 1.226228 | 0.0001790860 |
42101008601 | 0.130041 | 0.0000860222 |
42101008602 | 0.698585 | 0.0000781921 |
42101008701 | 0.195734 | 0.0000947767 |
42101008702 | 0.303340 | 0.0000670451 |
42101008801 | 0.264323 | 0.0000582363 |
42101008802 | 0.248908 | 0.0001679390 |
42101009000 | 0.185860 | 0.0001632627 |
42101009100 | 0.448475 | 0.0000764793 |
42101009200 | 0.798593 | 0.0000859678 |
42101009300 | 1.292196 | 0.0001280273 |
42101009400 | 1.630209 | 0.0001142431 |
42101009500 | 1.559226 | 0.0000878166 |
42101009600 | 1.489295 | 0.0001203604 |
42101009801 | 1.120167 | 0.0000627222 |
42101009802 | 1.239187 | 0.0001659815 |
42101010000 | 1.366909 | 0.0001298761 |
42101010100 | 1.684340 | 0.0001852576 |
42101010200 | 1.594933 | 0.0000898557 |
42101010300 | 1.617878 | 0.0000765608 |
42101010400 | 1.477662 | 0.0001004045 |
42101010500 | 1.330476 | 0.0001202516 |
42101010600 | 1.339162 | 0.0000451861 |
42101010700 | 1.453041 | 0.0000965982 |
42101010800 | 1.235375 | 0.0001124487 |
42101010900 | 0.849274 | 0.0000746849 |
42101011000 | 1.332465 | 0.0000877622 |
42101011100 | 1.504152 | 0.0000966798 |
42101011200 | 1.585709 | 0.0001612508 |
42101011300 | 1.625940 | 0.0000909160 |
42101011400 | 1.666356 | 0.0001854480 |
42101011500 | 1.614728 | 0.0001192457 |
42101011700 | 0.293101 | 0.0000526628 |
42101011800 | 1.539895 | 0.0001503485 |
42101011900 | 1.626101 | 0.0001358302 |
42101012000 | 0.528876 | 0.0000507596 |
42101012100 | 0.806919 | 0.0000848259 |
42101012201 | 0.436212 | 0.0000701173 |
42101012203 | 0.767771 | 0.0000163399 |
42101012204 | 0.923927 | 0.0001129925 |
42101012500 | 0.227612 | 0.0001426544 |
42101013100 | 0.631174 | 0.0000456755 |
42101013200 | 0.567809 | 0.0000732983 |
42101013300 | 0.113282 | 0.0000809653 |
42101013401 | 0.177468 | 0.0000672354 |
42101013402 | 0.041179 | 0.0000810468 |
42101013500 | 0.032426 | 0.0001077996 |
42101013601 | 0.156016 | 0.0000750927 |
42101013602 | 0.137295 | 0.0000945863 |
42101013700 | 0.573151 | 0.0001366187 |
42101013800 | 0.849168 | 0.0000497537 |
42101013900 | 0.632435 | 0.0000454036 |
42101014000 | 0.609400 | 0.0001028514 |
42101014100 | 0.752478 | 0.0000701445 |
42101014200 | 0.023144 | 0.0001370809 |
42101014300 | 0.107145 | 0.0000518199 |
42101014400 | 0.164564 | 0.0001185660 |
42101014500 | 1.117404 | 0.0000505149 |
42101014600 | 0.385644 | 0.0001102465 |
42101014700 | 0.350032 | 0.0000710417 |
42101014800 | 1.425649 | 0.0000214512 |
42101014900 | 1.155054 | 0.0001024708 |
42101015101 | 1.318134 | 0.0000613629 |
42101015102 | 1.584468 | 0.0001136178 |
42101015200 | 1.419901 | 0.0001449925 |
42101015300 | 0.158260 | 0.0001080171 |
42101015600 | 1.008325 | 0.0000430927 |
42101015700 | 0.226950 | 0.0000670995 |
42101015800 | 0.148003 | 0.0001872152 |
42101016000 | 0.104437 | 0.0001884930 |
42101016100 | 0.216298 | 0.0001605983 |
42101016200 | 1.190650 | 0.0000569312 |
42101016300 | 1.254316 | 0.0000816721 |
42101016400 | 1.269741 | 0.0001160919 |
42101016500 | 1.439876 | 0.0000861853 |
42101016600 | 0.974941 | 0.0000591606 |
42101016701 | 1.624670 | 0.0000737605 |
42101016702 | 1.312813 | 0.0000735158 |
42101016800 | 1.712118 | 0.0000789262 |
42101016901 | 1.734318 | 0.0000840647 |
42101016902 | 1.718854 | 0.0001193816 |
42101017000 | 0.734809 | 0.0000755549 |
42101017100 | 1.506335 | 0.0000933629 |
42101017201 | 1.386730 | 0.0000672898 |
42101017202 | 1.704054 | 0.0001036127 |
42101017300 | 1.358293 | 0.0000678336 |
42101017400 | 1.295769 | 0.0000618250 |
42101017500 | 1.522051 | 0.0001855839 |
42101017601 | 1.768306 | 0.0001333290 |
42101017602 | 1.550809 | 0.0001251454 |
42101017701 | 0.949778 | 0.0000851794 |
42101017702 | 1.455692 | 0.0001407240 |
42101017800 | 0.535425 | 0.0001542636 |
42101017900 | 0.715352 | 0.0001696519 |
42101018001 | 0.171881 | 0.0000832762 |
42101018002 | 0.184051 | 0.0001595108 |
42101018300 | 0.309510 | 0.0001077724 |
42101018400 | 0.230658 | 0.0000606560 |
42101018800 | 0.843924 | 0.0002358813 |
42101019000 | 1.054744 | 0.0002095363 |
42101019100 | 1.004639 | 0.0002227768 |
42101019200 | 0.962111 | 0.0002371048 |
42101019501 | 1.633057 | 0.0001204691 |
42101019502 | 1.462269 | 0.0000974954 |
42101019700 | 1.228175 | 0.0001920546 |
42101019800 | 1.191424 | 0.0001841429 |
42101019900 | 1.285865 | 0.0001217741 |
42101020000 | 1.097441 | 0.0000354257 |
42101020101 | 1.303429 | 0.0000946135 |
42101020102 | 1.614565 | 0.0000922754 |
42101020200 | 1.353189 | 0.0001253629 |
42101020300 | 1.312116 | 0.0000752286 |
42101020400 | 1.577853 | 0.0000725370 |
42101020500 | 1.410797 | 0.0000697639 |
42101020600 | 0.012822 | 0.0000448871 |
42101020700 | 0.060519 | 0.0001530673 |
42101020800 | 0.199100 | 0.0000609550 |
42101020900 | 0.046407 | 0.0000823246 |
42101021000 | 0.055904 | 0.0001422737 |
42101021100 | 0.079124 | 0.0000660663 |
42101021200 | 0.011846 | 0.0000655226 |
42101021300 | 0.061652 | 0.0000913510 |
42101021400 | 0.056142 | 0.0001039661 |
42101021500 | 0.061267 | 0.0001014105 |
42101021600 | 0.035389 | 0.0000614172 |
42101021700 | 0.045065 | 0.0001456178 |
42101021800 | 0.094191 | 0.0001289789 |
42101021900 | 0.159053 | 0.0000386610 |
42101022000 | 0.071095 | 0.0000417061 |
42101023100 | 0.208580 | 0.0000336041 |
42101023500 | 0.149380 | 0.0000339304 |
42101023600 | 0.143122 | 0.0000618250 |
42101023700 | 0.558469 | 0.0001116331 |
42101023800 | 0.614321 | 0.0001186204 |
42101023900 | 0.484316 | 0.0000435277 |
42101024000 | 0.411355 | 0.0000971420 |
42101024100 | 0.846494 | 0.0000374920 |
42101024200 | 1.102341 | 0.0001022261 |
42101024300 | 1.113886 | 0.0001021717 |
42101024400 | 1.025072 | 0.0000862125 |
42101024500 | 1.343803 | 0.0001036127 |
42101024600 | 1.190108 | 0.0000705795 |
42101024700 | 1.444767 | 0.0001139984 |
42101024800 | 1.530400 | 0.0000575566 |
42101024900 | 1.712417 | 0.0000733255 |
42101025200 | 1.318097 | 0.0002077420 |
42101025300 | 1.199693 | 0.0001240851 |
42101025400 | 1.150732 | 0.0001070112 |
42101025500 | 0.351852 | 0.0000697367 |
42101025600 | 0.186141 | 0.0000698726 |
42101025700 | 0.137727 | 0.0001024708 |
42101025800 | 1.459393 | 0.0000478233 |
42101025900 | 1.675203 | 0.0001166356 |
42101026000 | 1.503251 | 0.0000787359 |
42101026100 | 1.580514 | 0.0000864028 |
42101026200 | 1.525836 | 0.0001028514 |
42101026301 | 1.641217 | 0.0000926016 |
42101026302 | 1.570355 | 0.0001339543 |
42101026400 | 1.744224 | 0.0001532848 |
42101026500 | 1.630581 | 0.0001328124 |
42101026600 | 1.690902 | 0.0001714734 |
42101026700 | 1.749929 | 0.0001840342 |
42101026800 | 1.029990 | 0.0001051624 |
42101026900 | 0.759018 | 0.0000552184 |
42101027000 | 1.138153 | 0.0000694104 |
42101027100 | 1.053606 | 0.0000740867 |
42101027200 | 1.075694 | 0.0001228345 |
42101027300 | 1.124334 | 0.0001552151 |
42101027401 | 1.005289 | 0.0000801496 |
42101027402 | 0.979010 | 0.0001834089 |
42101027500 | 1.087783 | 0.0001389568 |
42101027600 | 1.644571 | 0.0001106271 |
42101027700 | 1.582996 | 0.0001253629 |
42101027800 | 1.561791 | 0.0001229976 |
42101027901 | 1.630063 | 0.0001088327 |
42101027902 | 0.390340 | 0.0001073102 |
42101028000 | 1.625322 | 0.0001108175 |
42101028100 | 1.386374 | 0.0001197894 |
42101028200 | 1.039571 | 0.0001409415 |
42101028300 | 1.529578 | 0.0001684828 |
42101028400 | 1.254799 | 0.0001035311 |
42101028500 | 1.060556 | 0.0000665557 |
42101028600 | 1.062329 | 0.0001768566 |
42101028700 | 1.249338 | 0.0000695192 |
42101028800 | 1.133221 | 0.0001230520 |
42101028901 | 1.301277 | 0.0001083706 |
42101028902 | 0.981556 | 0.0001843061 |
42101029000 | 0.981773 | 0.0002143486 |
42101029100 | 1.055548 | 0.0001386850 |
42101029200 | 0.836952 | 0.0001270214 |
42101029300 | 0.765070 | 0.0000846628 |
42101029400 | 0.742181 | 0.0001053255 |
42101029800 | 0.595533 | 0.0001305558 |
42101029900 | 0.673931 | 0.0001137266 |
42101030000 | 0.785256 | 0.0001981990 |
42101030100 | 0.544222 | 0.0001561667 |
42101030200 | 0.887594 | 0.0002299544 |
42101030501 | 0.756321 | 0.0001596467 |
42101030502 | 0.756302 | 0.0001907496 |
42101030600 | 0.307853 | 0.0001867802 |
42101030700 | 0.239082 | 0.0001108990 |
42101030800 | 0.211156 | 0.0001425728 |
42101030900 | 0.474975 | 0.0001178863 |
42101031000 | 0.364926 | 0.0001935771 |
42101031101 | 0.557003 | 0.0001385762 |
42101031102 | 0.768686 | 0.0001152491 |
42101031200 | 0.628785 | 0.0001319696 |
42101031300 | 0.367463 | 0.0002012713 |
42101031401 | 0.464355 | 0.0001686459 |
42101031402 | 0.713340 | 0.0001599186 |
42101031501 | 0.283489 | 0.0001799560 |
42101031502 | 0.169786 | 0.0001139169 |
42101031600 | 0.072007 | 0.0001600002 |
42101031700 | 0.160204 | 0.0001325133 |
42101031800 | 0.495670 | 0.0001061683 |
42101031900 | 0.309944 | 0.0001490979 |
42101032000 | 0.124171 | 0.0001951540 |
42101032100 | 0.219179 | 0.0001074190 |
42101032300 | 0.270887 | 0.0000965711 |
42101032500 | 0.103268 | 0.0001586952 |
42101032600 | 0.069488 | 0.0002018694 |
42101032900 | 0.090844 | 0.0000945320 |
42101033000 | 0.159393 | 0.0002207921 |
42101033101 | 0.038240 | 0.0001341990 |
42101033102 | 0.058571 | 0.0001053527 |
42101033200 | 0.229881 | 0.0000783280 |
42101033300 | 0.005905 | 0.0001090231 |
42101033400 | 0.297583 | 0.0001502398 |
42101033500 | 0.254600 | 0.0001036671 |
42101033600 | 0.029787 | 0.0001943656 |
42101033701 | 0.097137 | 0.0001699237 |
42101033702 | 0.300807 | 0.0001252814 |
42101033800 | 0.058250 | 0.0001575533 |
42101033900 | 0.068625 | 0.0000836568 |
42101034000 | 0.045834 | 0.0000836568 |
42101034100 | 0.062569 | 0.0001532576 |
42101034200 | 0.020873 | 0.0000901004 |
42101034400 | 0.197730 | 0.0002177471 |
42101034501 | 0.142368 | 0.0001125575 |
42101034502 | 0.038892 | 0.0001504573 |
42101034600 | 0.205840 | 0.0000660120 |
42101034701 | 0.066659 | 0.0001749807 |
42101034702 | 0.054391 | 0.0001036943 |
42101034801 | 0.075340 | 0.0001243842 |
42101034802 | 0.104325 | 0.0001424641 |
42101034803 | 0.090914 | 0.0001162006 |
42101034900 | 0.107673 | 0.0001381956 |
42101035100 | 0.060283 | 0.0001132644 |
42101035200 | 0.161275 | 0.0001272933 |
42101035301 | 0.135556 | 0.0001492610 |
42101035302 | 0.041350 | 0.0001197622 |
42101035500 | 0.102258 | 0.0002039900 |
42101035601 | 0.244977 | 0.0001420019 |
42101035602 | 0.245678 | 0.0000980120 |
42101035701 | 0.376102 | 0.0001262058 |
42101035702 | 0.287027 | 0.0001057605 |
42101035800 | 0.214236 | 0.0001725066 |
42101035900 | 0.217349 | 0.0001430350 |
42101036000 | 0.340816 | 0.0000909704 |
42101036100 | 0.020509 | 0.0001092134 |
42101036201 | 0.103859 | 0.0001338183 |
42101036202 | 0.041007 | 0.0001689722 |
42101036203 | 0.118953 | 0.0001362652 |
42101036301 | 0.234139 | 0.0001048633 |
42101036302 | 0.056693 | 0.0000985830 |
42101036303 | 0.133219 | 0.0001792220 |
42101036400 | 0.021616 | 0.0000272694 |
42101036501 | 0.028555 | 0.0001415669 |
42101036502 | 0.180353 | 0.0001131012 |
42101036600 | 0.097442 | 0.0000663654 |
42101036700 | 0.034993 | 0.0000957554 |
42101036900 | 0.220444 | 0.0001510282 |
42101037200 | 0.335554 | 0.0001235685 |
42101037300 | 0.055130 | 0.0001563026 |
42101037500 | 0.174149 | 0.0000979304 |
42101037600 | 0.310016 | 0.0000870009 |
42101037700 | 0.335639 | 0.0001425184 |
42101037800 | 0.083138 | 0.0000659576 |
42101037900 | 0.224960 | 0.0001358302 |
42101038000 | 0.276030 | 0.0000660935 |
42101038100 | 0.105334 | 0.0000224571 |
42101038200 | 0.149942 | 0.0000818081 |
42101038300 | 1.176136 | 0.0000896654 |
42101038400 | 0.092355 | 0.0000667732 |
42101038500 | 0.152944 | 0.0000470349 |
42101038600 | 0.051208 | 0.0000373288 |
42101038700 | 0.044611 | 0.0000740867 |
42101038800 | 0.082836 | 0.0000924657 |
42101038900 | 1.392375 | 0.0000853153 |
42101039000 | 0.791411 | 0.0002289756 |
42101980000 | 0.015962 | 0.0000109023 |
42101980100 | 0.374206 | 0.0000006797 |
42101980200 | 0.059038 | 0.0000150620 |
42101989100 | 0.907194 | 0.0000489924 |
42107003000 | 0.236517 | 0.0001421378 |
42115032000 | 0.286947 | 0.0000710145 |
42115032100 | 0.311138 | 0.0001022533 |
42115032200 | 0.306661 | 0.0001040749 |
42115032901 | 0.281649 | 0.0001070655 |
42115032902 | 0.154717 | 0.0000510315 |
42125704100 | 0.040330 | 0.0000507596 |
42125713700 | 0.353037 | 0.0001180494 |
42125714000 | 0.230627 | 0.0000700630 |
42125715700 | 0.254428 | 0.0000443161 |
42125722700 | 0.289624 | 0.0000952389 |
42125731000 | 0.316996 | 0.0001636705 |
42125732000 | 0.357717 | 0.0000872728 |
42125741100 | 0.344601 | 0.0001163366 |
42125741300 | 0.293167 | 0.0000943417 |
42125742100 | 0.263878 | 0.0001598099 |
42125742200 | 0.337887 | 0.0000470893 |
42125743700 | 0.150542 | 0.0000357520 |
42125744100 | 0.101413 | 0.0001510282 |
42125744200 | 0.140262 | 0.0000859950 |
42125745100 | 0.230537 | 0.0002370232 |
42125745200 | 0.219457 | 0.0001460800 |
42125746100 | 0.233879 | 0.0001638337 |
42125746200 | 0.295622 | 0.0001218829 |
42125746301 | 0.257639 | 0.0001421650 |
42125746302 | 0.217313 | 0.0001630180 |
42125751100 | 0.324692 | 0.0001333561 |
42125751200 | 0.250135 | 0.0000850978 |
42125752700 | 0.258324 | 0.0001219916 |
42125753700 | 0.099384 | 0.0000524996 |
42125754200 | 0.145658 | 0.0000811556 |
42125754300 | 0.104177 | 0.0000622057 |
42125754400 | 0.163405 | 0.0000458114 |
42125754500 | 0.150819 | 0.0000667460 |
42125754600 | 0.050181 | 0.0000440170 |
42125755100 | 0.155210 | 0.0001090774 |
42125755200 | 0.257948 | 0.0001452100 |
42125755700 | 0.286554 | 0.0000965439 |
42125771100 | 0.285133 | 0.0001618490 |
42125771200 | 0.335031 | 0.0000814275 |
42125795800 | 0.274770 | 0.0001241667 |
42127960300 | 0.219879 | 0.0000668276 |
42129800100 | 0.277576 | 0.0000262906 |
42129800200 | 0.111964 | 0.0000340119 |
42129800300 | 0.163023 | 0.0000612813 |
42129800400 | 0.262694 | 0.0000391504 |
42129800500 | 0.308848 | 0.0000666101 |
42129800600 | 0.076191 | 0.0000639729 |
42129800700 | 0.103832 | 0.0000511131 |
42129800800 | 0.255333 | 0.0000451317 |
42129800900 | 0.235638 | 0.0000652779 |
42129801001 | 0.322920 | 0.0001053255 |
42129801002 | 0.259340 | 0.0000633204 |
42129801100 | 0.292795 | 0.0001347427 |
42129801200 | 0.354958 | 0.0001524692 |
42129801300 | 0.208082 | 0.0001179135 |
42129801400 | 0.328968 | 0.0000458930 |
42129801500 | 0.222518 | 0.0000707970 |
42129801600 | 0.113442 | 0.0000330060 |
42129801701 | 0.255337 | 0.0000648701 |
42129801702 | 0.320569 | 0.0001193544 |
42129801703 | 0.237708 | 0.0000723739 |
42129801800 | 0.283692 | 0.0001604080 |
42129801900 | 0.356379 | 0.0001740291 |
42129802001 | 0.168034 | 0.0000678607 |
42129802002 | 0.310000 | 0.0002059747 |
42129802101 | 0.318375 | 0.0001282448 |
42129802102 | 0.195581 | 0.0001577436 |
42129802103 | 0.227618 | 0.0000669907 |
42129802200 | 0.328135 | 0.0000800137 |
42129802301 | 0.264533 | 0.0001591574 |
42129802303 | 0.332079 | 0.0000803671 |
42129802304 | 0.303364 | 0.0001732406 |
42129802400 | 0.270331 | 0.0001094581 |
42129802500 | 0.222909 | 0.0000510315 |
42129802600 | 0.095124 | 0.0000901275 |
42129802700 | 0.202011 | 0.0000520646 |
42129802800 | 0.170761 | 0.0000508956 |
42129802900 | 0.301737 | 0.0001463519 |
42129803000 | 0.275369 | 0.0001256892 |
42129803100 | 0.290466 | 0.0001021717 |
42129803200 | 0.346095 | 0.0000637826 |
42129803301 | 0.283696 | 0.0001617130 |
42129803302 | 0.281785 | 0.0001015736 |
42129803400 | 0.194920 | 0.0000958914 |
42129803501 | 0.229369 | 0.0001328124 |
42129803502 | 0.317622 | 0.0001041564 |
42129803600 | 0.289182 | 0.0000492915 |
42129803700 | 0.301681 | 0.0001112525 |
42129803800 | 0.326815 | 0.0001490707 |
42129803901 | 0.263821 | 0.0000835753 |
42129803902 | 0.213528 | 0.0000922754 |
42129804000 | 0.098267 | 0.0000332507 |
42129804100 | 0.145060 | 0.0000678336 |
42129804200 | 0.166603 | 0.0000954564 |
42129804300 | 0.218352 | 0.0000573391 |
42129804400 | 0.286074 | 0.0000584266 |
42129804501 | 0.270592 | 0.0001308549 |
42129804502 | 0.266480 | 0.0001495601 |
42129804600 | 0.314251 | 0.0000785999 |
42129804701 | 0.318423 | 0.0000797146 |
42129804702 | 0.264002 | 0.0001534207 |
42129804801 | 0.259690 | 0.0000584538 |
42129804802 | 0.325376 | 0.0001654921 |
42129804900 | 0.259536 | 0.0001354768 |
42129805000 | 0.338148 | 0.0000982023 |
42129805100 | 0.345440 | 0.0000696008 |
42129805902 | 0.238832 | 0.0001756875 |
42129806000 | 0.180358 | 0.0000719389 |
42129806100 | 0.267704 | 0.0000938795 |
42129806300 | 0.321646 | 0.0000503246 |
42129806400 | 0.332225 | 0.0000613357 |
42129806500 | 0.315969 | 0.0001294683 |
42129806600 | 0.337229 | 0.0000785999 |
42129806700 | 0.247984 | 0.0000756908 |
42129806800 | 0.222573 | 0.0000400204 |
42129806900 | 0.301511 | 0.0001034768 |
42129807000 | 0.369765 | 0.0000914054 |
42129807100 | 0.374206 | 0.0000886866 |
42129807200 | 0.304521 | 0.0002028210 |
42129807300 | 0.355926 | 0.0001253086 |
42129807401 | 0.297277 | 0.0000581547 |
42129807402 | 0.218281 | 0.0002080138 |
42129807500 | 0.338349 | 0.0000594869 |
42129807600 | 0.311643 | 0.0000664742 |
42129807700 | 0.333502 | 0.0000865931 |
42129807800 | 0.293863 | 0.0001026611 |
42129807900 | 0.297779 | 0.0001688634 |
42129808100 | 0.143748 | 0.0001196535 |
42129808200 | 0.326829 | 0.0000688939 |
42131400300 | 0.185898 | 0.0001182125 |
42131400700 | 0.357828 | 0.0001040205 |
42133000100 | 0.205464 | 0.0000297978 |
42133000200 | 0.298986 | 0.0000746305 |
42133000300 | 0.579010 | 0.0000575838 |
42133000400 | 0.178501 | 0.0000533153 |
42133000500 | 0.278837 | 0.0000693289 |
42133000600 | 0.452372 | 0.0000835209 |
42133000700 | 1.036921 | 0.0000965439 |
42133000800 | 0.248642 | 0.0000526899 |
42133000900 | 0.202076 | 0.0000890672 |
42133001000 | 0.388529 | 0.0000395311 |
42133001100 | 0.303458 | 0.0000934173 |
42133001200 | 0.237958 | 0.0000851794 |
42133001300 | 0.116441 | 0.0000861038 |
42133001400 | 0.048308 | 0.0000988820 |
42133001500 | 0.628232 | 0.0000863484 |
42133001600 | 0.279853 | 0.0000407001 |
42133010110 | 0.034471 | 0.0002561362 |
42133010120 | 0.047566 | 0.0001198166 |
42133010130 | 0.173745 | 0.0000988820 |
42133010210 | 0.086413 | 0.0000793068 |
42133010220 | 0.072832 | 0.0001495329 |
42133010300 | 0.045618 | 0.0000471165 |
42133010400 | 0.116670 | 0.0000970876 |
42133010510 | 0.113002 | 0.0001428175 |
42133010520 | 0.239957 | 0.0000605472 |
42133020100 | 0.060074 | 0.0000873816 |
42133020220 | 0.212594 | 0.0001178863 |
42133020221 | 0.133249 | 0.0001362380 |
42133020222 | 0.252229 | 0.0001219916 |
42133020310 | 0.269947 | 0.0000708514 |
42133020410 | 0.208823 | 0.0001378965 |
42133020420 | 0.205862 | 0.0002416451 |
42133020521 | 0.110185 | 0.0001648940 |
42133020522 | 0.256086 | 0.0001060324 |
42133020600 | 0.272737 | 0.0002013528 |
42133020710 | 0.136556 | 0.0001636433 |
42133020720 | 0.148671 | 0.0002702195 |
42133020800 | 0.025832 | 0.0002210640 |
42133020910 | 0.176938 | 0.0001719084 |
42133020921 | 0.206597 | 0.0001970300 |
42133020922 | 0.298655 | 0.0001060868 |
42133021010 | 0.156820 | 0.0001286255 |
42133021020 | 0.209166 | 0.0001905865 |
42133021100 | 0.052234 | 0.0001282720 |
42133021210 | 0.085098 | 0.0002248431 |
42133021220 | 0.301411 | 0.0001940937 |
42133021300 | 0.032372 | 0.0001165269 |
42133021410 | 0.082191 | 0.0001371352 |
42133021420 | 0.116215 | 0.0001945287 |
42133021500 | 0.155897 | 0.0000958098 |
42133021600 | 0.156847 | 0.0000752830 |
42133021711 | 0.283427 | 0.0000820528 |
42133021712 | 0.232867 | 0.0001721531 |
42133021720 | 0.119599 | 0.0001197351 |
42133022600 | 0.176367 | 0.0002324828 |
42133022700 | 0.055476 | 0.0001700869 |
42133022800 | 0.219916 | 0.0002057301 |
42133022910 | 0.019823 | 0.0002631507 |
42133022920 | 0.199361 | 0.0001190282 |
42133023000 | 0.171596 | 0.0001325405 |
42133023100 | 0.209389 | 0.0001683196 |
42133023200 | 0.175082 | 0.0001634802 |
42133023301 | 0.104744 | 0.0001819407 |
42133023302 | 0.169350 | 0.0001741650 |
42133023400 | 0.194056 | 0.0003029808 |
42133023500 | 0.221833 | 0.0002901482 |
42133023601 | 0.272637 | 0.0002042347 |
42133023602 | 0.277655 | 0.0002630147 |
42133023710 | 0.319566 | 0.0001040477 |
42133023721 | 0.239191 | 0.0001624743 |
47001020100 | 0.033250 | 0.0000821343 |
47001020201 | 0.172760 | 0.0001080987 |
47001020202 | 0.134728 | 0.0001073918 |
47001020300 | 0.152050 | 0.0000947767 |
47001020400 | 0.168562 | 0.0001079356 |
47001020500 | 0.020335 | 0.0000896654 |
47001020600 | 0.051165 | 0.0000675889 |
47001020902 | 0.304214 | 0.0001764488 |
47001021000 | 0.267804 | 0.0001670418 |
47001021100 | 0.205943 | 0.0001079356 |
47001021201 | 0.190804 | 0.0001416212 |
47001021202 | 0.201082 | 0.0001421106 |
47001021301 | 0.303032 | 0.0000981208 |
47001021302 | 0.221937 | 0.0001915924 |
47009010100 | 0.019991 | 0.0000766424 |
47009010200 | 0.137497 | 0.0001707937 |
47009010301 | 0.117012 | 0.0001483366 |
47009010302 | 0.126260 | 0.0000936076 |
47009010400 | 0.260034 | 0.0000907257 |
47009010500 | 0.100730 | 0.0000720748 |
47009010600 | 0.141817 | 0.0001146509 |
47009010700 | 0.141220 | 0.0001330571 |
47009010800 | 0.176484 | 0.0000778930 |
47009010900 | 0.125549 | 0.0001689178 |
47009011001 | 0.228174 | 0.0001633715 |
47009011002 | 0.333987 | 0.0001186204 |
47009011101 | 0.288758 | 0.0001352049 |
47009011102 | 0.327791 | 0.0002405848 |
47009011200 | 0.234523 | 0.0002444183 |
47009011301 | 0.250566 | 0.0001610877 |
47009011302 | 0.223225 | 0.0001577164 |
47009011401 | 0.270906 | 0.0000440986 |
47009011402 | 0.337793 | 0.0001207682 |
47009011502 | 0.230176 | 0.0001083162 |
47009011503 | 0.289946 | 0.0001860189 |
47009011602 | 0.239078 | 0.0002425151 |
47009011603 | 0.289842 | 0.0001308549 |
47009011604 | 0.242559 | 0.0001126934 |
47009011605 | 0.127954 | 0.0000940426 |
47009980100 | 0.173204 | 0.0000001088 |
47019070100 | 0.244005 | 0.0000475786 |
47019070200 | 0.135740 | 0.0000995345 |
47019070300 | 0.105320 | 0.0001452100 |
47019070400 | 0.284094 | 0.0000573663 |
47019070500 | 0.332015 | 0.0001064946 |
47019070600 | 0.277204 | 0.0000616891 |
47019070700 | 0.350818 | 0.0000967614 |
47019070800 | 0.096654 | 0.0000776755 |
47019070900 | 0.217411 | 0.0000933085 |
47019071000 | 0.374206 | 0.0000735702 |
47019071100 | 0.365548 | 0.0000528531 |
47019071200 | 0.345379 | 0.0001079627 |
47019071300 | 0.337305 | 0.0002185627 |
47019071400 | 0.269411 | 0.0000884963 |
47019071500 | 0.340074 | 0.0000546747 |
47019071600 | 0.320321 | 0.0000400748 |
47037010105 | 0.876436 | 0.0001181310 |
47037010106 | 0.610643 | 0.0000913782 |
47037010201 | 0.205066 | 0.0001118778 |
47037010202 | 0.109765 | 0.0001044555 |
47037010301 | 0.155525 | 0.0000909704 |
47037010302 | 0.110567 | 0.0000581275 |
47037010303 | 0.050572 | 0.0001279186 |
47037010401 | 0.226629 | 0.0001308549 |
47037010402 | 0.261338 | 0.0001787326 |
47037010501 | 0.039977 | 0.0001329211 |
47037010502 | 0.042156 | 0.0001524692 |
47037010601 | 0.214066 | 0.0001405881 |
47037010602 | 0.293904 | 0.0001054615 |
47037010701 | 0.235337 | 0.0001090503 |
47037010702 | 0.202765 | 0.0000816450 |
47037010801 | 0.199060 | 0.0001391471 |
47037010802 | 0.063730 | 0.0000994530 |
47037010901 | 0.161371 | 0.0000891760 |
47037010903 | 1.178645 | 0.0001548617 |
47037010904 | 1.054184 | 0.0000870553 |
47037011001 | 0.511979 | 0.0001783519 |
47037011002 | 0.319381 | 0.0000669092 |
47037011100 | 0.130893 | 0.0001095396 |
47037011200 | 0.047390 | 0.0001048905 |
47037011300 | 0.301623 | 0.0001524964 |
47037011400 | 0.406641 | 0.0001238132 |
47037011500 | 0.095856 | 0.0000978489 |
47037011600 | 0.109637 | 0.0001331386 |
47037011700 | 0.092436 | 0.0001526595 |
47037011800 | 0.625314 | 0.0000727545 |
47037011900 | 0.372090 | 0.0000675889 |
47037012100 | 0.206220 | 0.0000666373 |
47037012200 | 0.206074 | 0.0000560069 |
47037012600 | 0.491384 | 0.0000569584 |
47037012701 | 1.244519 | 0.0001622296 |
47037012702 | 1.202413 | 0.0000775940 |
47037012801 | 1.216942 | 0.0001434156 |
47037012802 | 0.739174 | 0.0001183485 |
47037013000 | 0.176794 | 0.0000231912 |
47037013100 | 0.140345 | 0.0000651691 |
47037013201 | 0.168421 | 0.0000788174 |
47037013202 | 0.030231 | 0.0000885778 |
47037013300 | 0.056290 | 0.0001076637 |
47037013400 | 0.222263 | 0.0001191369 |
47037013500 | 0.078625 | 0.0000600035 |
47037013601 | 1.251104 | 0.0000881972 |
47037013602 | 1.120122 | 0.0000484215 |
47037013700 | 1.011082 | 0.0001674496 |
47037013800 | 1.353174 | 0.0000549465 |
47037013900 | 1.215277 | 0.0000433917 |
47037014200 | 0.869538 | 0.0000527987 |
47037014300 | 0.936827 | 0.0000499984 |
47037014400 | 0.663813 | 0.0000554087 |
47037014800 | 1.591420 | 0.0000883332 |
47037015100 | 0.132805 | 0.0001007308 |
47037015200 | 0.053543 | 0.0000714495 |
47037015300 | 0.037965 | 0.0001598371 |
47037015401 | 0.020261 | 0.0001525779 |
47037015402 | 0.053834 | 0.0001263145 |
47037015404 | 0.024628 | 0.0000757452 |
47037015405 | 0.030195 | 0.0001296042 |
47037015501 | 0.034065 | 0.0000828684 |
47037015502 | 0.080518 | 0.0000991811 |
47037015609 | 0.126189 | 0.0001254717 |
47037015610 | 0.095559 | 0.0002437386 |
47037015612 | 0.308347 | 0.0001830011 |
47037015613 | 0.262989 | 0.0001394462 |
47037015614 | 0.147437 | 0.0001102737 |
47037015615 | 0.371531 | 0.0001465422 |
47037015617 | 0.102378 | 0.0000666373 |
47037015618 | 0.261763 | 0.0001718541 |
47037015619 | 0.102874 | 0.0001365099 |
47037015620 | 0.299553 | 0.0001873511 |
47037015622 | 0.118658 | 0.0001166085 |
47037015623 | 0.036341 | 0.0001397996 |
47037015624 | 0.130119 | 0.0001405337 |
47037015625 | 0.030536 | 0.0001552967 |
47037015626 | 0.260202 | 0.0001779441 |
47037015627 | 0.219757 | 0.0000784912 |
47037015628 | 0.449533 | 0.0001014920 |
47037015629 | 0.259418 | 0.0001883299 |
47037015630 | 0.492184 | 0.0001179950 |
47037015631 | 0.185798 | 0.0003205169 |
47037015700 | 0.241357 | 0.0000446695 |
47037015802 | 0.144242 | 0.0001420290 |
47037015803 | 0.370959 | 0.0000755005 |
47037015804 | 0.363332 | 0.0001072559 |
47037015900 | 0.029059 | 0.0000759627 |
47037016000 | 0.321656 | 0.0000245778 |
47037016100 | 0.232506 | 0.0000628310 |
47037016200 | 0.620321 | 0.0000815906 |
47037016300 | 0.232652 | 0.0000675889 |
47037016400 | 0.035343 | 0.0001128294 |
47037016500 | 0.047630 | 0.0001274564 |
47037016600 | 0.143122 | 0.0000830315 |
47037016700 | 0.159057 | 0.0001417572 |
47037016800 | 0.106012 | 0.0001274564 |
47037016900 | 0.158550 | 0.0001357215 |
47037017000 | 0.068691 | 0.0000989092 |
47037017100 | 0.152854 | 0.0000773493 |
47037017200 | 0.168104 | 0.0000380901 |
47037017300 | 0.265224 | 0.0000908616 |
47037017401 | 0.201955 | 0.0000619338 |
47037017402 | 0.139906 | 0.0001437419 |
47037017500 | 0.091119 | 0.0000788446 |
47037017701 | 0.207464 | 0.0000656042 |
47037017702 | 0.155721 | 0.0001398268 |
47037017800 | 0.116576 | 0.0001455091 |
47037017901 | 0.182489 | 0.0001305286 |
47037017902 | 0.212766 | 0.0001271573 |
47037018000 | 0.196044 | 0.0001307461 |
47037018101 | 0.201758 | 0.0001352049 |
47037018102 | 0.174139 | 0.0000983926 |
47037018201 | 0.188496 | 0.0000781649 |
47037018202 | 0.027455 | 0.0001902874 |
47037018203 | 0.168740 | 0.0000370298 |
47037018301 | 0.063874 | 0.0002195958 |
47037018302 | 0.241224 | 0.0000722380 |
47037018401 | 0.056880 | 0.0001896077 |
47037018404 | 0.016925 | 0.0001318336 |
47037018405 | 0.139058 | 0.0001238948 |
47037018407 | 0.088112 | 0.0001341718 |
47037018408 | 0.109003 | 0.0000967070 |
47037018409 | 0.109161 | 0.0001125031 |
47037018410 | 0.031198 | 0.0000927376 |
47037018500 | 0.307946 | 0.0001315346 |
47037018601 | 0.230047 | 0.0000671267 |
47037018602 | 0.231761 | 0.0001123944 |
47037018700 | 0.265215 | 0.0000863484 |
47037018801 | 0.172075 | 0.0001557861 |
47037018803 | 0.086729 | 0.0000981208 |
47037018804 | 0.094355 | 0.0001344165 |
47037018901 | 0.007276 | 0.0000794699 |
47037018902 | 0.099316 | 0.0000659848 |
47037018904 | 0.063939 | 0.0000999967 |
47037018905 | 0.293968 | 0.0000830859 |
47037019003 | 0.283265 | 0.0001201972 |
47037019004 | 0.236954 | 0.0001269398 |
47037019005 | 0.462310 | 0.0000864028 |
47037019006 | 0.357950 | 0.0001420562 |
47037019105 | 0.183101 | 0.0001625015 |
47037019106 | 0.006552 | 0.0001027155 |
47037019108 | 0.699609 | 0.0000966526 |
47037019109 | 0.331723 | 0.0001412950 |
47037019110 | 0.117722 | 0.0000995889 |
47037019111 | 0.283737 | 0.0001145150 |
47037019112 | 0.183685 | 0.0001253629 |
47037019114 | 0.040969 | 0.0003708144 |
47037019115 | 0.075438 | 0.0001028242 |
47037019116 | 0.034640 | 0.0001689178 |
47037019117 | 0.107824 | 0.0001397181 |
47037019118 | 0.304073 | 0.0001720444 |
47037019200 | 0.097955 | 0.0001036127 |
47037019300 | 0.995431 | 0.0000864844 |
47037019400 | 0.071256 | 0.0001523060 |
47037019500 | 0.027603 | 0.0002117657 |
47037019600 | 0.183790 | 0.0001021989 |
47047060702 | 0.099959 | 0.0000894207 |
47065000400 | 1.348126 | 0.0000920851 |
47065000600 | 0.195612 | 0.0000983383 |
47065000700 | 0.268220 | 0.0001220460 |
47065000800 | 0.060647 | 0.0000463280 |
47065001100 | 0.432006 | 0.0000409720 |
47065001200 | 1.092092 | 0.0000799049 |
47065001300 | 0.367845 | 0.0000537775 |
47065001400 | 0.205813 | 0.0000464639 |
47065001600 | 1.040522 | 0.0000684045 |
47065001800 | 0.012348 | 0.0000647885 |
47065001900 | 1.315663 | 0.0001000239 |
47065002000 | 0.073751 | 0.0000399932 |
47065002300 | 0.315747 | 0.0000438539 |
47065002400 | 0.353909 | 0.0001458897 |
47065002500 | 0.546638 | 0.0001328124 |
47065002600 | 0.654180 | 0.0000616075 |
47065002800 | 0.043589 | 0.0000966798 |
47065002900 | 0.350665 | 0.0000734886 |
47065003000 | 0.168745 | 0.0000554087 |
47065003100 | 0.072182 | 0.0000536415 |
47065003200 | 1.060482 | 0.0000709330 |
47065003300 | 0.823143 | 0.0001728328 |
47065003400 | 0.034691 | 0.0001021174 |
47065010101 | 0.180160 | 0.0001645134 |
47065010103 | 0.271130 | 0.0001051352 |
47065010201 | 0.292609 | 0.0001026339 |
47065010303 | 0.258338 | 0.0000841734 |
47065010304 | 0.278801 | 0.0001318064 |
47065010305 | 0.207570 | 0.0000931998 |
47065010306 | 0.263760 | 0.0001073646 |
47065010307 | 0.261372 | 0.0001477385 |
47065010411 | 0.198080 | 0.0002007819 |
47065010412 | 0.162791 | 0.0001418115 |
47065010413 | 0.214456 | 0.0001023621 |
47065010431 | 0.102050 | 0.0001975465 |
47065010432 | 0.133710 | 0.0001877317 |
47065010433 | 0.056093 | 0.0001210673 |
47065010434 | 0.371195 | 0.0000620426 |
47065010435 | 0.116659 | 0.0001501582 |
47065010501 | 0.101358 | 0.0001590486 |
47065010502 | 0.135585 | 0.0000840919 |
47065010600 | 0.148140 | 0.0000801224 |
47065010700 | 0.078347 | 0.0000706883 |
47065010800 | 0.075509 | 0.0001049449 |
47065010901 | 0.197340 | 0.0000514121 |
47065010902 | 0.104271 | 0.0000266984 |
47065010903 | 0.124098 | 0.0001657096 |
47065011001 | 0.374206 | 0.0000491283 |
47065011002 | 0.250751 | 0.0002107054 |
47065011100 | 0.306493 | 0.0001667156 |
47065011201 | 0.057236 | 0.0003282111 |
47065011203 | 0.070920 | 0.0001802551 |
47065011204 | 0.086115 | 0.0001529314 |
47065011311 | 0.020528 | 0.0002564625 |
47065011314 | 0.062252 | 0.0001513273 |
47065011321 | 0.052217 | 0.0002015703 |
47065011323 | 0.040579 | 0.0001691625 |
47065011324 | 0.067800 | 0.0001258251 |
47065011325 | 0.050645 | 0.0001541004 |
47065011326 | 0.091218 | 0.0001465966 |
47065011402 | 0.507512 | 0.0001692168 |
47065011411 | 0.277936 | 0.0001140800 |
47065011413 | 0.116497 | 0.0002235381 |
47065011442 | 0.125366 | 0.0000839831 |
47065011443 | 0.023195 | 0.0001565201 |
47065011444 | 1.285354 | 0.0000978489 |
47065011445 | 0.094641 | 0.0000952117 |
47065011446 | 0.013647 | 0.0001252814 |
47065011447 | 0.068957 | 0.0002252509 |
47065011600 | 0.074285 | 0.0001482279 |
47065011700 | 0.031190 | 0.0001218285 |
47065011800 | 0.020712 | 0.0001717181 |
47065011900 | 0.039362 | 0.0000378182 |
47065012000 | 0.293344 | 0.0000530706 |
47065012100 | 0.119541 | 0.0001769382 |
47065012200 | 1.404129 | 0.0000641088 |
47065012300 | 0.563164 | 0.0001221820 |
47065012400 | 0.056146 | 0.0001765032 |
47093000100 | 0.142733 | 0.0000652235 |
47093000800 | 0.093994 | 0.0000948582 |
47093000901 | 0.045121 | 0.0000515753 |
47093000902 | 0.127414 | 0.0000814275 |
47093001400 | 0.122904 | 0.0000632932 |
47093001500 | 0.039904 | 0.0000869466 |
47093001600 | 0.103337 | 0.0000771862 |
47093001700 | 0.030186 | 0.0000610910 |
47093001800 | 0.131439 | 0.0000576653 |
47093001900 | 0.567549 | 0.0000346644 |
47093002000 | 0.976196 | 0.0000734342 |
47093002100 | 0.666149 | 0.0000800681 |
47093002200 | 0.190438 | 0.0001019814 |
47093002300 | 0.027219 | 0.0000806390 |
47093002400 | 0.052930 | 0.0001091590 |
47093002600 | 0.106310 | 0.0000692745 |
47093002700 | 0.062693 | 0.0000777027 |
47093002800 | 0.119585 | 0.0001161191 |
47093002900 | 0.120256 | 0.0000934173 |
47093003000 | 0.040360 | 0.0001239220 |
47093003100 | 0.083429 | 0.0000675889 |
47093003200 | 0.450041 | 0.0000756365 |
47093003300 | 0.120015 | 0.0000564962 |
47093003400 | 0.241759 | 0.0001091318 |
47093003500 | 0.083002 | 0.0001322143 |
47093003700 | 0.183484 | 0.0000699270 |
47093003801 | 0.018069 | 0.0001259611 |
47093003802 | 0.064837 | 0.0000826237 |
47093003901 | 0.046359 | 0.0001072287 |
47093003902 | 0.025513 | 0.0000827053 |
47093004000 | 0.065951 | 0.0001136722 |
47093004100 | 0.079926 | 0.0001108718 |
47093004200 | 0.147126 | 0.0000840103 |
47093004300 | 0.107422 | 0.0000752558 |
47093004401 | 0.146253 | 0.0001286798 |
47093004403 | 0.167514 | 0.0001354224 |
47093004404 | 0.114251 | 0.0001059508 |
47093004500 | 0.068732 | 0.0001753885 |
47093004606 | 0.159073 | 0.0001867802 |
47093004607 | 0.052261 | 0.0001742194 |
47093004608 | 0.100839 | 0.0000731895 |
47093004609 | 0.030425 | 0.0001411590 |
47093004610 | 0.023076 | 0.0001436331 |
47093004611 | 0.114424 | 0.0001223179 |
47093004612 | 0.054220 | 0.0000681870 |
47093004613 | 0.062231 | 0.0001517623 |
47093004614 | 0.046203 | 0.0000797690 |
47093004615 | 0.025945 | 0.0001177503 |
47093004700 | 0.088731 | 0.0001117418 |
47093004800 | 0.090904 | 0.0001560308 |
47093004900 | 0.159309 | 0.0001400443 |
47093005000 | 0.178482 | 0.0001099474 |
47093005100 | 0.210897 | 0.0001866986 |
47093005201 | 0.107307 | 0.0001876502 |
47093005202 | 0.039323 | 0.0000979576 |
47093005301 | 0.185795 | 0.0001252542 |
47093005302 | 0.244223 | 0.0001001055 |
47093005401 | 0.193608 | 0.0000938523 |
47093005402 | 0.325599 | 0.0000813187 |
47093005501 | 0.214992 | 0.0000681054 |
47093005502 | 0.284484 | 0.0000930638 |
47093005602 | 0.288371 | 0.0001002686 |
47093005603 | 0.244638 | 0.0000958642 |
47093005604 | 0.277722 | 0.0000771318 |
47093005701 | 0.236758 | 0.0001278370 |
47093005704 | 0.154930 | 0.0001795754 |
47093005706 | 0.151015 | 0.0001142431 |
47093005707 | 0.232106 | 0.0000893119 |
47093005708 | 0.160547 | 0.0000829772 |
47093005709 | 0.214335 | 0.0000528259 |
47093005710 | 0.165212 | 0.0000598403 |
47093005711 | 0.203909 | 0.0001552423 |
47093005712 | 0.138225 | 0.0002285678 |
47093005803 | 0.192746 | 0.0000791709 |
47093005807 | 0.126090 | 0.0000759627 |
47093005808 | 0.131160 | 0.0001476297 |
47093005809 | 0.231033 | 0.0001435788 |
47093005810 | 0.215022 | 0.0001003502 |
47093005811 | 0.289360 | 0.0000930638 |
47093005812 | 0.150859 | 0.0001734581 |
47093005813 | 0.204994 | 0.0001694343 |
47093005903 | 0.203813 | 0.0001130197 |
47093005904 | 0.122586 | 0.0001630724 |
47093005905 | 0.108747 | 0.0000720477 |
47093005906 | 0.279006 | 0.0000563059 |
47093005907 | 0.144502 | 0.0001239764 |
47093005908 | 0.170168 | 0.0001339815 |
47093006001 | 0.144728 | 0.0001117147 |
47093006002 | 0.137291 | 0.0001593205 |
47093006003 | 0.285947 | 0.0001221004 |
47093006102 | 0.200959 | 0.0001408328 |
47093006103 | 0.168131 | 0.0001278914 |
47093006104 | 0.232441 | 0.0001465694 |
47093006202 | 0.303468 | 0.0001342533 |
47093006203 | 0.220736 | 0.0001427631 |
47093006205 | 0.333517 | 0.0001212576 |
47093006206 | 0.255181 | 0.0001389025 |
47093006207 | 0.193592 | 0.0000948582 |
47093006208 | 0.184473 | 0.0001575261 |
47093006301 | 0.315019 | 0.0000976314 |
47093006302 | 0.319680 | 0.0000733527 |
47093006401 | 0.258721 | 0.0001105728 |
47093006402 | 0.345360 | 0.0001425456 |
47093006403 | 0.236638 | 0.0000810468 |
47093006501 | 0.247509 | 0.0000797962 |
47093006502 | 0.281809 | 0.0000953748 |
47093006600 | 0.070065 | 0.0000897197 |
47093006700 | 0.311550 | 0.0000794156 |
47093006800 | 0.598796 | 0.0001195719 |
47093006900 | 0.062529 | 0.0002131251 |
47093007000 | 0.510900 | 0.0000721836 |
47093007100 | 0.196302 | 0.0000983383 |
47105060100 | 0.245087 | 0.0001430078 |
47105060201 | 0.140427 | 0.0001162006 |
47105060202 | 0.199966 | 0.0002076332 |
47105060301 | 0.177621 | 0.0001254173 |
47105060302 | 0.303124 | 0.0001687003 |
47105060400 | 0.299033 | 0.0001445303 |
47105060501 | 0.335056 | 0.0002297369 |
47105060502 | 0.275656 | 0.0000604928 |
47105060600 | 0.189520 | 0.0001322958 |
47105060700 | 0.129562 | 0.0000681054 |
47125100100 | 0.075124 | 0.0000310485 |
47125100200 | 0.095280 | 0.0000389601 |
47125100300 | 0.085380 | 0.0001444760 |
47125100400 | 0.285829 | 0.0000803128 |
47125100500 | 0.070328 | 0.0001219645 |
47125100601 | 0.183778 | 0.0000551912 |
47125100602 | 0.082464 | 0.0000654954 |
47125100700 | 0.110209 | 0.0000346644 |
47125100800 | 0.387577 | 0.0000683501 |
47125100900 | 0.171186 | 0.0000592422 |
47125101001 | 0.044025 | 0.0001061683 |
47125101002 | 0.006801 | 0.0000913238 |
47125101101 | 0.040201 | 0.0000665829 |
47125101102 | 0.041731 | 0.0002050775 |
47125101103 | 0.021286 | 0.0000673714 |
47125101201 | 0.086617 | 0.0000554359 |
47125101202 | 0.008747 | 0.0001093221 |
47125101303 | 0.096647 | 0.0002785118 |
47125101304 | 0.245616 | 0.0001511641 |
47125101305 | 0.135793 | 0.0001404793 |
47125101306 | 0.104761 | 0.0001412678 |
47125101307 | 0.009755 | 0.0000604113 |
47125101400 | 0.077112 | 0.0001599186 |
47125101600 | 0.063609 | 0.0001557045 |
47125101802 | 0.178225 | 0.0002929757 |
47125101803 | 0.090113 | 0.0001847955 |
47125101804 | 0.109620 | 0.0002011625 |
47125101902 | 0.031860 | 0.0000638369 |
47125101903 | 0.015999 | 0.0002779137 |
47125101904 | 0.033340 | 0.0001374343 |
47125102001 | 0.032493 | 0.0001423009 |
47125102002 | 0.027794 | 0.0002351201 |
47125102003 | 0.106019 | 0.0001826476 |
47125102004 | 0.118277 | 0.0001633443 |
47125102005 | 0.100013 | 0.0001375974 |
47125102006 | 0.039210 | 0.0002392254 |
47125980100 | 0.072782 | 0.0000071776 |
47129110400 | 0.358087 | 0.0001142975 |
47145030100 | 0.126437 | 0.0000869194 |
47145030900 | 0.325181 | 0.0001751166 |
47147080103 | 0.150641 | 0.0001675856 |
47147080104 | 0.266474 | 0.0002037182 |
47147080603 | 0.192020 | 0.0001240579 |
47147080604 | 0.199512 | 0.0001044827 |
47147080605 | 0.178015 | 0.0000833034 |
47147080606 | 0.153033 | 0.0001545354 |
47149040101 | 0.391609 | 0.0000949398 |
47149040102 | 0.100537 | 0.0001055430 |
47149040103 | 0.091849 | 0.0002075245 |
47149040104 | 0.129212 | 0.0001516263 |
47149040105 | 0.127959 | 0.0001103553 |
47149040200 | 0.019106 | 0.0001077996 |
47149040302 | 0.071984 | 0.0004878034 |
47149040303 | 0.026505 | 0.0000672626 |
47149040304 | 0.028841 | 0.0000832218 |
47149040305 | 0.065047 | 0.0000734614 |
47149040306 | 0.036206 | 0.0001477657 |
47149040307 | 0.117749 | 0.0000803128 |
47149040308 | 0.019486 | 0.0001737300 |
47149040403 | 0.056328 | 0.0001903961 |
47149040501 | 0.091993 | 0.0002363435 |
47149040502 | 0.182276 | 0.0001964862 |
47149040701 | 0.122404 | 0.0003194838 |
47149040702 | 0.122371 | 0.0001781344 |
47149040805 | 0.013881 | 0.0002606222 |
47149040806 | 0.073710 | 0.0002195143 |
47149040807 | 0.083825 | 0.0003407175 |
47149040808 | 0.100040 | 0.0002356910 |
47149040809 | 0.243612 | 0.0001194088 |
47149040901 | 0.057873 | 0.0001847139 |
47149040902 | 0.028942 | 0.0004290234 |
47149040903 | 0.031176 | 0.0003355518 |
47149040904 | 0.036023 | 0.0001224810 |
47149040905 | 0.021163 | 0.0002967004 |
47149041000 | 0.152519 | 0.0004507193 |
47149041101 | 0.075329 | 0.0002061107 |
47149041102 | 0.050019 | 0.0000755005 |
47149041201 | 0.067492 | 0.0001448022 |
47149041202 | 0.065799 | 0.0001237045 |
47149041301 | 0.147628 | 0.0001514088 |
47149041302 | 0.085154 | 0.0001649212 |
47149041401 | 0.040590 | 0.0001169075 |
47149041402 | 0.142567 | 0.0001983894 |
47149041403 | 0.041860 | 0.0002602144 |
47149041500 | 0.155199 | 0.0000658488 |
47149041600 | 0.066318 | 0.0001492610 |
47149041700 | 0.050067 | 0.0001480919 |
47149041800 | 0.018415 | 0.0001099746 |
47149041900 | 0.242651 | 0.0001157928 |
47149042000 | 0.021718 | 0.0001309092 |
47149042100 | 0.046594 | 0.0002630419 |
47149042200 | 0.024985 | 0.0001384403 |
47149042300 | 0.031288 | 0.0004875859 |
47153060200 | 0.291686 | 0.0001059780 |
47155080201 | 0.293243 | 0.0002214990 |
47155080202 | 0.224653 | 0.0001504029 |
47155080300 | 0.243505 | 0.0001569823 |
47155080400 | 0.206899 | 0.0001929518 |
47157000100 | 0.079323 | 0.0001468141 |
47157000200 | 1.755343 | 0.0000228921 |
47157000300 | 1.729417 | 0.0000208530 |
47157000400 | 1.708782 | 0.0000367579 |
47157000600 | 1.819540 | 0.0000484215 |
47157000700 | 1.601552 | 0.0001170435 |
47157000800 | 1.699148 | 0.0000637010 |
47157000900 | 1.656466 | 0.0000614716 |
47157001100 | 0.518116 | 0.0000857775 |
47157001200 | 0.347400 | 0.0001123672 |
47157001300 | 0.707553 | 0.0000780290 |
47157001400 | 1.571660 | 0.0000420051 |
47157001500 | 0.888613 | 0.0000461105 |
47157001600 | 0.039083 | 0.0000867291 |
47157001700 | 0.382225 | 0.0001016552 |
47157001900 | 1.740414 | 0.0000310757 |
47157002000 | 1.270803 | 0.0000491012 |
47157002100 | 1.075624 | 0.0000347460 |
47157002400 | 1.218914 | 0.0000588344 |
47157002500 | 0.258073 | 0.0000703892 |
47157002600 | 0.085163 | 0.0000721836 |
47157002700 | 0.382406 | 0.0000570400 |
47157002800 | 1.140729 | 0.0000842006 |
47157002900 | 0.232569 | 0.0001329211 |
47157003000 | 0.262769 | 0.0000781105 |
47157003100 | 0.058789 | 0.0000904538 |
47157003200 | 0.034731 | 0.0001020358 |
47157003300 | 0.221298 | 0.0000640273 |
47157003400 | 0.078663 | 0.0000595141 |
47157003500 | 0.031469 | 0.0000819712 |
47157003600 | 0.147000 | 0.0000415158 |
47157003700 | 0.781549 | 0.0000309397 |
47157003800 | 0.804372 | 0.0000204996 |
47157003900 | 0.843261 | 0.0000415701 |
47157004200 | 0.067816 | 0.0000878981 |
47157004300 | 0.129340 | 0.0000739236 |
47157004500 | 1.321238 | 0.0000301513 |
47157004600 | 1.252288 | 0.0000315650 |
47157005000 | 1.703845 | 0.0000258012 |
47157005300 | 1.741587 | 0.0000859406 |
47157005500 | 1.605440 | 0.0000572575 |
47157005600 | 1.779904 | 0.0001111165 |
47157005700 | 1.673547 | 0.0000755821 |
47157005800 | 1.593040 | 0.0000203093 |
47157005900 | 1.731201 | 0.0000609279 |
47157006000 | 1.580285 | 0.0000502702 |
47157006200 | 1.617447 | 0.0000435549 |
47157006300 | 0.191076 | 0.0000733255 |
47157006400 | 1.530805 | 0.0000479593 |
47157006500 | 1.680142 | 0.0000661207 |
47157006600 | 0.123855 | 0.0000565778 |
47157006700 | 1.623895 | 0.0000973323 |
47157006800 | 1.688657 | 0.0000535871 |
47157006900 | 1.768865 | 0.0000711233 |
47157007000 | 0.750482 | 0.0000824878 |
47157007100 | 0.182118 | 0.0000705523 |
47157007200 | 0.185245 | 0.0000735702 |
47157007300 | 0.164765 | 0.0001170707 |
47157007400 | 0.062239 | 0.0000852337 |
47157007500 | 1.715819 | 0.0000392864 |
47157007810 | 1.767015 | 0.0000653867 |
47157007821 | 1.737756 | 0.0001336008 |
47157007822 | 1.245611 | 0.0000476874 |
47157007900 | 1.534978 | 0.0001401259 |
47157008000 | 0.688174 | 0.0001149500 |
47157008110 | 1.130734 | 0.0000624232 |
47157008120 | 1.592712 | 0.0001334649 |
47157008200 | 1.128746 | 0.0001287070 |
47157008500 | 0.152726 | 0.0001184029 |
47157008600 | 0.052655 | 0.0001642959 |
47157008700 | 0.132252 | 0.0001298489 |
47157008800 | 0.432912 | 0.0001855295 |
47157008900 | 0.676437 | 0.0001232151 |
47157009100 | 0.645716 | 0.0000883332 |
47157009200 | 0.143585 | 0.0002045338 |
47157009300 | 0.047588 | 0.0001179135 |
47157009400 | 0.055097 | 0.0000919763 |
47157009500 | 0.213928 | 0.0001573358 |
47157009600 | 0.044901 | 0.0001477385 |
47157009700 | 0.589474 | 0.0000743586 |
47157009800 | 0.171194 | 0.0000867019 |
47157009901 | 0.498795 | 0.0000691114 |
47157009902 | 0.965077 | 0.0000487477 |
47157010000 | 1.361810 | 0.0001968940 |
47157010110 | 1.279408 | 0.0001721531 |
47157010120 | 1.443590 | 0.0001482007 |
47157010210 | 1.412185 | 0.0001480647 |
47157010220 | 1.152735 | 0.0002299544 |
47157010300 | 1.605133 | 0.0000383620 |
47157010500 | 0.980290 | 0.0000516024 |
47157010610 | 1.057334 | 0.0001603808 |
47157010620 | 1.369704 | 0.0001016280 |
47157010630 | 1.021139 | 0.0001112525 |
47157010710 | 0.961567 | 0.0001395006 |
47157010720 | 1.129939 | 0.0001053799 |
47157010810 | 1.048807 | 0.0001604896 |
47157010820 | 1.306218 | 0.0001147053 |
47157011010 | 1.053025 | 0.0001003230 |
47157011020 | 1.309123 | 0.0000390417 |
47157011100 | 1.577578 | 0.0000441258 |
47157011200 | 1.747588 | 0.0000370570 |
47157011300 | 0.887289 | 0.0000356976 |
47157011400 | 1.001164 | 0.0001375703 |
47157011500 | 1.311141 | 0.0000675617 |
47157011600 | 1.628970 | 0.0000755005 |
47157011700 | 1.521203 | 0.0000352082 |
47157011800 | 0.321474 | 0.0001552423 |
47157020101 | 0.665650 | 0.0001027155 |
47157020102 | 0.125198 | 0.0000730264 |
47157020210 | 0.051758 | 0.0001514088 |
47157020221 | 0.124259 | 0.0000644623 |
47157020222 | 0.226573 | 0.0000783280 |
47157020300 | 0.057623 | 0.0001330843 |
47157020400 | 0.075768 | 0.0000321904 |
47157020511 | 1.041645 | 0.0000605200 |
47157020512 | 1.228813 | 0.0001432253 |
47157020521 | 1.496881 | 0.0000885778 |
47157020523 | 1.298174 | 0.0000782737 |
47157020524 | 1.316090 | 0.0001297402 |
47157020531 | 1.019291 | 0.0001510554 |
47157020532 | 1.064053 | 0.0001725881 |
47157020541 | 1.042289 | 0.0001463791 |
47157020542 | 1.396933 | 0.0001409415 |
47157020610 | 0.631257 | 0.0001145694 |
47157020621 | 0.721269 | 0.0002204115 |
47157020622 | 0.095319 | 0.0001177503 |
47157020632 | 0.029426 | 0.0001562483 |
47157020633 | 0.151768 | 0.0000777299 |
47157020634 | 0.105445 | 0.0000833850 |
47157020635 | 0.165261 | 0.0000628038 |
47157020642 | 0.168152 | 0.0002743521 |
47157020643 | 0.075838 | 0.0002290844 |
47157020644 | 0.354809 | 0.0002515143 |
47157020651 | 0.093386 | 0.0001729959 |
47157020652 | 0.047911 | 0.0001359390 |
47157020700 | 0.138870 | 0.0000596500 |
47157020820 | 0.003749 | 0.0002284591 |
47157020831 | 0.045754 | 0.0000939610 |
47157020832 | 0.059966 | 0.0002724761 |
47157020900 | 0.040365 | 0.0002728839 |
47157021010 | 0.392281 | 0.0004748892 |
47157021020 | 0.173269 | 0.0001775363 |
47157021111 | 0.349489 | 0.0001250095 |
47157021112 | 0.419848 | 0.0001818048 |
47157021113 | 0.237885 | 0.0001066305 |
47157021121 | 0.634624 | 0.0001409959 |
47157021122 | 0.354753 | 0.0001723706 |
47157021124 | 0.345422 | 0.0001950181 |
47157021125 | 0.131793 | 0.0001179407 |
47157021126 | 0.164009 | 0.0001294411 |
47157021135 | 0.381440 | 0.0001854751 |
47157021136 | 0.123177 | 0.0001476025 |
47157021137 | 0.127848 | 0.0002149739 |
47157021138 | 0.455530 | 0.0001086424 |
47157021139 | 0.096106 | 0.0001126119 |
47157021140 | 0.078977 | 0.0001405337 |
47157021141 | 0.323334 | 0.0001899068 |
47157021142 | 0.170032 | 0.0000958370 |
47157021200 | 0.678823 | 0.0000514393 |
47157021311 | 0.158217 | 0.0001281089 |
47157021312 | 0.099565 | 0.0000570400 |
47157021320 | 0.124918 | 0.0001652746 |
47157021331 | 0.130638 | 0.0000837656 |
47157021333 | 0.432532 | 0.0001310724 |
47157021334 | 0.802447 | 0.0001189466 |
47157021341 | 0.168688 | 0.0001402618 |
47157021342 | 0.193391 | 0.0002759289 |
47157021351 | 0.260275 | 0.0001219645 |
47157021352 | 0.305974 | 0.0001592933 |
47157021353 | 0.207503 | 0.0002573053 |
47157021410 | 0.264164 | 0.0000799321 |
47157021420 | 0.179810 | 0.0000787087 |
47157021430 | 0.131245 | 0.0001171794 |
47157021510 | 0.824732 | 0.0002348482 |
47157021520 | 0.291881 | 0.0003546648 |
47157021530 | 0.189620 | 0.0001467597 |
47157021540 | 0.159699 | 0.0003253020 |
47157021611 | 0.056724 | 0.0001723706 |
47157021612 | 0.298384 | 0.0001228073 |
47157021613 | 0.094522 | 0.0001270486 |
47157021620 | 0.364725 | 0.0000862669 |
47157021710 | 1.480395 | 0.0000847987 |
47157021721 | 1.395603 | 0.0001198166 |
47157021724 | 1.392040 | 0.0000588888 |
47157021725 | 1.267326 | 0.0001251998 |
47157021726 | 0.853054 | 0.0000917316 |
47157021731 | 1.295768 | 0.0000877078 |
47157021732 | 1.316697 | 0.0001653018 |
47157021741 | 1.239088 | 0.0002379748 |
47157021744 | 0.986701 | 0.0001594836 |
47157021745 | 1.118462 | 0.0002196230 |
47157021746 | 1.258723 | 0.0001278098 |
47157021747 | 1.233992 | 0.0001123944 |
47157021751 | 1.210090 | 0.0001964862 |
47157021752 | 1.400782 | 0.0001333018 |
47157021753 | 1.386909 | 0.0000696008 |
47157021754 | 1.115578 | 0.0001191369 |
47157021900 | 1.698861 | 0.0001378149 |
47157022022 | 1.690942 | 0.0001213935 |
47157022023 | 1.619478 | 0.0000393679 |
47157022024 | 1.526241 | 0.0000911335 |
47157022111 | 1.538691 | 0.0001358574 |
47157022112 | 1.596959 | 0.0001680478 |
47157022121 | 1.559542 | 0.0001240851 |
47157022122 | 1.625885 | 0.0001092949 |
47157022130 | 1.739778 | 0.0001582058 |
47157022210 | 1.706708 | 0.0001132644 |
47157022220 | 1.605014 | 0.0000992083 |
47157022310 | 1.776330 | 0.0001667428 |
47157022321 | 1.693548 | 0.0000973867 |
47157022322 | 1.697383 | 0.0001052983 |
47157022330 | 1.584888 | 0.0001339815 |
47157022410 | 1.409635 | 0.0001656552 |
47157022500 | 1.206927 | 0.0001391471 |
47157022600 | 1.045733 | 0.0001076909 |
47157022700 | 1.745143 | 0.0002003741 |
47157980100 | 0.249801 | 0.0000022294 |
47157980400 | 1.083168 | 0.0000643535 |
47163043301 | 0.279091 | 0.0001609246 |
47163043302 | 0.312440 | 0.0001632355 |
47163043600 | 0.217236 | 0.0001312355 |
47165020403 | 0.307925 | 0.0000533696 |
47165020405 | 0.289295 | 0.0000626407 |
47165020406 | 0.314028 | 0.0001046730 |
47165020407 | 0.185660 | 0.0001227529 |
47165020501 | 0.140192 | 0.0001636705 |
47165020502 | 0.145048 | 0.0001484182 |
47165020503 | 0.126270 | 0.0000593238 |
47165020601 | 0.189261 | 0.0001025796 |
47165020602 | 0.158815 | 0.0001233510 |
47165020603 | 0.130966 | 0.0000895022 |
47165020700 | 0.056705 | 0.0001496144 |
47165020800 | 0.305209 | 0.0001910758 |
47165020901 | 0.067567 | 0.0000370570 |
47165020902 | 0.012849 | 0.0001847683 |
47165020903 | 0.097255 | 0.0001030961 |
47165021002 | 0.050941 | 0.0001988787 |
47165021004 | 0.031482 | 0.0001245201 |
47165021005 | 0.197480 | 0.0001669874 |
47165021006 | 0.194078 | 0.0000974411 |
47165021007 | 0.054283 | 0.0000901547 |
47165021008 | 0.140941 | 0.0001617946 |
47165021009 | 0.087248 | 0.0001478200 |
47165021103 | 0.140352 | 0.0001679662 |
47165021104 | 0.087126 | 0.0000563603 |
47165021105 | 0.095088 | 0.0001550520 |
47165021106 | 0.013055 | 0.0001166356 |
47165021107 | 0.123616 | 0.0001302024 |
47165021201 | 0.168854 | 0.0001836536 |
47165021203 | 0.157243 | 0.0002073069 |
47165021204 | 0.113281 | 0.0001975737 |
47165021205 | 0.194237 | 0.0000749024 |
47171080300 | 0.229495 | 0.0001399628 |
47179060100 | 0.028625 | 0.0000910519 |
47179060400 | 0.180027 | 0.0001605983 |
47179060501 | 0.149781 | 0.0001389568 |
47179060502 | 0.068705 | 0.0001577980 |
47179060600 | 0.059116 | 0.0001941481 |
47179060700 | 0.026707 | 0.0000509227 |
47179060800 | 0.067242 | 0.0000712320 |
47179060900 | 0.120745 | 0.0001553783 |
47179061000 | 0.091059 | 0.0000605200 |
47179061100 | 0.161225 | 0.0001171794 |
47179061200 | 0.072595 | 0.0001004589 |
47179061300 | 0.138607 | 0.0002194871 |
47179061401 | 0.177745 | 0.0001381956 |
47179061402 | 0.191342 | 0.0002011081 |
47179061500 | 0.275659 | 0.0002071438 |
47179061601 | 0.311584 | 0.0001222363 |
47179061701 | 0.131383 | 0.0001761497 |
47179061702 | 0.279578 | 0.0001827836 |
47179061800 | 0.335829 | 0.0001801735 |
47179061901 | 0.354419 | 0.0001964318 |
47179061902 | 0.228109 | 0.0001381140 |
47179062000 | 0.088824 | 0.0000967886 |
47187050101 | 0.088579 | 0.0002863147 |
47187050102 | 0.065396 | 0.0001405609 |
47187050203 | 0.152112 | 0.0001707666 |
47187050204 | 0.173628 | 0.0001513273 |
47187050205 | 0.130431 | 0.0000954020 |
47187050206 | 0.131564 | 0.0000784912 |
47187050207 | 0.177362 | 0.0001108175 |
47187050208 | 0.307091 | 0.0001992322 |
47187050303 | 0.216646 | 0.0000844453 |
47187050304 | 0.207760 | 0.0000647613 |
47187050305 | 0.150535 | 0.0000767783 |
47187050306 | 0.212801 | 0.0000552456 |
47187050307 | 0.150689 | 0.0000979576 |
47187050403 | 0.287476 | 0.0000538590 |
47187050404 | 0.270963 | 0.0001726969 |
47187050405 | 0.249837 | 0.0000697639 |
47187050406 | 0.240340 | 0.0001564658 |
47187050601 | 0.038524 | 0.0001716094 |
47187050602 | 0.092018 | 0.0003158406 |
47187050701 | 0.167905 | 0.0001141072 |
47187050702 | 0.179619 | 0.0001254989 |
47187050800 | 0.061905 | 0.0001705219 |
47187050904 | 0.073693 | 0.0001531760 |
47187050905 | 0.108474 | 0.0001597827 |
47187050906 | 0.231674 | 0.0001531217 |
47187050907 | 0.088108 | 0.0001471675 |
47187050908 | 0.154536 | 0.0001117418 |
47187050909 | 0.131212 | 0.0001109534 |
47187051001 | 0.175752 | 0.0001990147 |
47187051002 | 0.122095 | 0.0002341413 |
47189030203 | 0.115596 | 0.0001567920 |
47189030204 | 0.162678 | 0.0002293019 |
47189030303 | 0.110937 | 0.0001228073 |
47189030304 | 0.158425 | 0.0001761769 |
47189030305 | 0.224523 | 0.0001477385 |
47189030307 | 0.073131 | 0.0002537981 |
47189030308 | 0.063800 | 0.0001384131 |
47189030309 | 0.123341 | 0.0001530673 |
47189030901 | 0.117270 | 0.0003337846 |
47189030903 | 0.122548 | 0.0002750589 |
54003971101 | 0.048141 | 0.0001664437 |
54003971102 | 0.177785 | 0.0002610844 |
54003971201 | 0.080083 | 0.0002824268 |
54003971300 | 0.070095 | 0.0002605407 |
54003971400 | 0.085936 | 0.0002366426 |
54003971500 | 0.046163 | 0.0000877078 |
54003971600 | 0.057359 | 0.0001212576 |
54003971700 | 0.092970 | 0.0001436331 |
54003971800 | 0.324175 | 0.0002225593 |
54003971900 | 0.083408 | 0.0003012408 |
54003972000 | 0.072328 | 0.0003394668 |
54003972101 | 0.083138 | 0.0001478472 |
54003972102 | 0.095028 | 0.0003228279 |
54011000101 | 0.186081 | 0.0000442617 |
54011000102 | 0.134389 | 0.0000574206 |
54011000200 | 0.340457 | 0.0000749024 |
54011000300 | 0.296114 | 0.0000682142 |
54011000400 | 0.149014 | 0.0000598947 |
54011000500 | 0.072636 | 0.0000819984 |
54011000600 | 0.048217 | 0.0000372201 |
54011000900 | 0.155455 | 0.0000377095 |
54011001000 | 0.245802 | 0.0000513034 |
54011001100 | 0.209624 | 0.0000520103 |
54011001200 | 0.134886 | 0.0000755005 |
54011001300 | 0.093680 | 0.0000647341 |
54011001400 | 0.185853 | 0.0000629126 |
54011001500 | 0.220231 | 0.0000359423 |
54011001600 | 0.149697 | 0.0000315378 |
54011001800 | 0.117059 | 0.0000965711 |
54011001900 | 0.191371 | 0.0000599491 |
54011002000 | 0.266251 | 0.0000762618 |
54011002100 | 0.310806 | 0.0000841734 |
54011010102 | 0.237301 | 0.0001593205 |
54011010201 | 0.231883 | 0.0001607886 |
54011010202 | 0.194171 | 0.0001014649 |
54011010300 | 0.264864 | 0.0000738964 |
54011010400 | 0.194551 | 0.0001728600 |
54011010500 | 0.325480 | 0.0001595924 |
54011010600 | 0.307891 | 0.0001063315 |
54011010700 | 0.342839 | 0.0001916196 |
54011010800 | 0.368828 | 0.0001791132 |
54011010900 | 0.049899 | 0.0000408904 |
54037972201 | 0.110229 | 0.0001300120 |
54037972300 | 0.106987 | 0.0001244385 |
54039000100 | 0.146586 | 0.0000325710 |
54039000200 | 0.130696 | 0.0000547018 |
54039000300 | 0.265890 | 0.0000732711 |
54039000500 | 0.204598 | 0.0000575838 |
54039000600 | 0.127263 | 0.0000949670 |
54039000700 | 0.498395 | 0.0000568497 |
54039000800 | 0.060571 | 0.0000408633 |
54039000900 | 0.084263 | 0.0000299881 |
54039001100 | 0.086532 | 0.0001203060 |
54039001200 | 0.166579 | 0.0000414070 |
54039001300 | 0.080809 | 0.0000580731 |
54039001500 | 0.109926 | 0.0001178591 |
54039001700 | 0.132143 | 0.0000438267 |
54039001800 | 0.076513 | 0.0000691114 |
54039001901 | 0.230303 | 0.0000935260 |
54039001902 | 0.260108 | 0.0000986101 |
54039002000 | 0.188734 | 0.0000753374 |
54039002100 | 0.135136 | 0.0001206323 |
54039010100 | 0.049436 | 0.0000908616 |
54039010200 | 0.080677 | 0.0000577197 |
54039010300 | 0.164846 | 0.0000586169 |
54039010400 | 0.435035 | 0.0000370026 |
54039010500 | 0.061992 | 0.0001173153 |
54039010600 | 0.335744 | 0.0001203604 |
54039010701 | 0.161934 | 0.0001244929 |
54039010702 | 0.225757 | 0.0001275380 |
54039010900 | 0.374206 | 0.0000757180 |
54039011000 | 0.288545 | 0.0001225898 |
54039011100 | 0.303765 | 0.0001264776 |
54039011200 | 0.327642 | 0.0001082890 |
54039011301 | 0.314913 | 0.0000903994 |
54039011302 | 0.320372 | 0.0001600274 |
54039011401 | 0.260671 | 0.0000777299 |
54039011402 | 0.312584 | 0.0001005133 |
54039011500 | 0.104560 | 0.0001070655 |
54039011800 | 0.269055 | 0.0001113340 |
54039012100 | 0.242773 | 0.0001094853 |
54039012200 | 0.263501 | 0.0001490707 |
54039012300 | 0.244771 | 0.0001901786 |
54039012800 | 0.103037 | 0.0001058693 |
54039012900 | 0.104664 | 0.0000296619 |
54039013000 | 0.163147 | 0.0001195719 |
54039013100 | 0.093194 | 0.0001014649 |
54039013200 | 0.276872 | 0.0001021446 |
54039013300 | 0.239066 | 0.0000712320 |
54039013400 | 0.230496 | 0.0000511674 |
54039013500 | 0.293907 | 0.0000669092 |
54039013600 | 0.252770 | 0.0001128294 |
54039013701 | 0.247288 | 0.0000521190 |
54039013702 | 0.292894 | 0.0001432525 |
54039013800 | 0.219685 | 0.0000705251 |
54079020100 | 0.374206 | 0.0001581242 |
54079020200 | 0.249462 | 0.0001278370 |
54079020300 | 0.337538 | 0.0002880819 |
54079020400 | 0.263780 | 0.0003568670 |
54079020500 | 0.291663 | 0.0001780529 |
54079020601 | 0.177825 | 0.0003165203 |
54079020603 | 0.212310 | 0.0003645884 |
54079020604 | 0.152007 | 0.0000689483 |
54079020605 | 0.329265 | 0.0002025219 |
54079020700 | 0.348569 | 0.0001216654 |
54099005100 | 0.237817 | 0.0000508684 |
54099005200 | 0.329822 | 0.0000473340 |
54099020100 | 0.161105 | 0.0000798777 |
54099020300 | 0.263845 | 0.0001213119 |
54099020400 | 0.352467 | 0.0001712831 |
54099020500 | 0.328512 | 0.0001317249 |
54099020600 | 0.344249 | 0.0001239492 |
54099020700 | 0.367199 | 0.0000993986 |
# Join Census tract data with local segregation indices on GEOID
tracts_segregation_indices <- tracts_data %>%
# Make sure both GEOID columns are of the same type
mutate(GEOID = as.character(GEOID)) %>%
inner_join(local_segregation_indices %>% mutate(GEOID = as.character(GEOID)), by = "GEOID")
# Function to generate segregation plot for a given state
plot_segregation <- function(state_code, tracts_data) {
tracts_segregation_indices %>%
filter(State == state_code) %>%
ggplot(aes(fill = ls)) +
geom_sf(color = "white", linewidth = 0.05) + # Add tract boundaries for better clarity
# NAD83 / Conus Albers (EPSG:5070) projection for better accuracy in the U.S.
coord_sf(crs = 5070) +
# Use viridis color scale for better perceptual uniformity
scale_fill_viridis_c(
option = "inferno",
name = "Segregation Index",
limits = c(0, 2), # Adjust based on data range
breaks = c(0.5, 1, 1.5, 2)) +
theme_minimal() + # Cleaner theme
theme(
plot.title = element_text(hjust = 0.5, size = 14), # Center the title
axis.text = element_text(size = 5), # Remove axis text
legend.position = "right", # Move the legend to the side
legend.title = element_text(size = 10), # Adjust legend title
legend.text = element_text(size = 8), # Adjust legend text size
plot.margin = margin(10, 10, 10, 10) # Add margins to avoid plot overlap
) +
labs(
fill = "Local\nSegregation Index", # Label for the legend
title = paste("Local Segregation Index for", state_code), # Dynamic plot title
caption = "Data Source: US Census Data"
)
}
# List of state codes to plot
states_to_plot <- c("OH", "PA", "TN", "WV", "KY", "IN", "IL")
# Generate and print the segregation plots for each state using map from purrr
segregation_plots <- purrr::map(states_to_plot, ~plot_segregation(.x, tracts_segregation_indices))
# Optionally, print the plots
purrr::walk(segregation_plots, print)The diversity gradient concept uses scatterplot smoothing to illustrate how neighborhood diversity changes with distance or travel time from the core of an urban region (K. Walker 2016b). Traditionally, social science literature on suburbanization suggests that urban cores are more diverse compared to the more segregated and homogeneous suburban neighborhoods. The diversity gradient serves as a visual tool to assess whether this demographic model holds true.
The entropy index for a given geographic unit is calculated as follows:
\[ E = \sum_{r=1}^{n} Q_r \log \frac{1}{Q_r} \]
Where \(Q_r\) represents group \(r\)’s proportion of the population in the geographic unit.
This statistic can be calculated using the entropy() function from the
segregation package. Since the entropy() function computes the
statistic for one unit at a time, we group the data by tract and use
group_modify() to calculate entropy for each tract individually. The
argument base = 4 represents the number of groups considered, setting
the maximum entropy value to 1, which indicates perfect evenness across
the four groups.
# Define the states for analysis
states <- c("OH", "PA", "TN", "WV", "KY", "IN", "IL")
# Initialize an empty list to store data for each state
state_data_list <- vector("list", length(states))
names(state_data_list) <- states
# Loop through each state to get tract data by race/ethnicity
state_data_list <- lapply(states, function(state) {
get_acs(
geography = "tract",
variables = c(
white = "B03002_003",
black = "B03002_004",
asian = "B03002_006",
hispanic = "B03002_012"
),
state = state,
geometry = TRUE,
year = 2019
)
})
# Combine data from all states
acs_data <- bind_rows(state_data_list)
# Get urbanized areas by population with geometry, filter for populations ≥ 750,000
us_urban_areas <- get_acs(
geography = "urban area",
variables = "B01001_001",
geometry = TRUE,
year = 2019,
survey = "acs1"
) %>%
filter(estimate >= 750000) %>%
transmute(urban_name = str_remove(NAME, fixed(" Urbanized Area (2010)")))
# Ensure the CRS is consistent between urban areas and tracts
us_urban_areas <- st_transform(us_urban_areas, crs = st_crs(acs_data))
# Compute an inner spatial join between tract data and urbanized areas
urban_data <- acs_data %>%
st_join(us_urban_areas, left = FALSE) %>%
select(-NAME) %>%
st_drop_geometry() %>%
mutate(dataset = "2015-2019 5-year ACS")
# Function to calculate entropy and plot diversity gradient for a given urban area
analyze_entropy <- function(urban_area_name) {
# Calculate entropy for each tract in the urban area
urban_entropy <- urban_data %>%
filter(urban_name == urban_area_name) %>%
group_by(GEOID) %>%
group_modify(~ data.frame(entropy = entropy(
data = .x,
group = "variable",
weight = "estimate",
base = 4)))
# Get tract geometry and join with entropy data
urban_entropy_geo <- tracts(state = unique(urban_data$state), cb = TRUE, year = 2019) %>%
inner_join(urban_entropy, by = "GEOID")
# Calculate the centroid of each tract
urban_entropy_geo <- urban_entropy_geo %>%
mutate(centroid = st_centroid(geometry))
# Calculate the centroid of the urban area
urban_centroid <- us_urban_areas %>%
filter(urban_name == urban_area_name) %>%
st_centroid() %>%
st_geometry()
# Ensure urban_centroid is of the same length as the number of tracts
urban_centroid <- rep(urban_centroid, nrow(urban_entropy_geo))
# Calculate distance to urban core centroid using tract centroids
urban_entropy_geo <- urban_entropy_geo %>%
mutate(distance_to_core = as.numeric(st_distance(centroid, urban_centroid, by_element = TRUE)))
# Plot diversity gradient with enhanced visualization
ggplot(urban_entropy_geo %>% na.omit(), aes(x = distance_to_core, y = entropy)) +
geom_point(alpha = 0.6, color = "dodgerblue", size = 3) +
geom_smooth(method = "loess", level = 0.95, color = "darkred", linetype = "dashed", fill = "lightpink") +
theme_minimal() +
theme(
plot.title = element_text(hjust = 0.5, size = 18, face = "bold"),
axis.title = element_text(size = 14, face = "bold"),
axis.text = element_text(size = 14),
panel.grid.major = element_line(color = "grey80"),
panel.grid.minor = element_blank()
) +
labs(title = paste("Diversity Gradient in", urban_area_name, "(Urbanized Area)"),
x = "Distance to Urban Core (meters)",
y = "Entropy Index") +
geom_rug(sides = "b", color = "darkgrey")
}
# Analyze and plot diversity gradients for major urban areas
urban_areas_to_analyze <- urban_data$urban_name %>% unique()
lapply(urban_areas_to_analyze, analyze_entropy)## [[1]]
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In this analysis, we will be working with US Census data to model regression for variables of interest such as median home value, median income, and several demographic factors. The data is pulled from the American Community Survey (ACS) and visualized through maps and histograms. In this section, we will focus on regression modeling for the state of Pennsylvania (PA). The data is sourced from the 2020 ACS 5-year estimates. We will visualize the data using geographic maps and histograms of median home values.
# Get all names for Pennsylvania counties
dfw_counties <- fips_codes %>%
filter(state == "PA") %>%
pull(county)
# Define the variables to retrieve from the ACS
variables_to_get <- c(
median_value = "B25077_001",
median_rooms = "B25018_001",
median_income = "DP03_0062",
total_population = "B01003_001",
median_age = "B01002_001",
pct_college = "DP02_0068P",
pct_foreign_born = "DP02_0094P",
pct_white = "DP05_0077P",
median_year_built = "B25037_001",
percent_ooh = "DP04_0046P"
)
# Get ACS data for Pennsylvania counties
dfw_data <- get_acs(
geography = "tract",
variables = variables_to_get,
state = "PA",
county = dfw_counties,
geometry = TRUE,
output = "wide",
year = 2020
) %>%
select(-NAME) ## Getting data from the 2016-2020 5-year ACS
## Fetching data by table type ("B/C", "S", "DP") and combining the result.
# Calculate population density and median structure age
dfw_data_for_model <- dfw_data %>%
# Calculate population density in people per square kilometer
mutate(population_density = as.numeric(set_units(total_populationE / st_area(.), "1/km2")),
median_structure_age = 2018 - median_year_builtE) %>%
select(!ends_with("M")) %>%
rename_with(.fn = ~str_remove(.x, "E$")) %>%
na.omit()In this section, we are performing a regression modeling analysis to understand the factors influencing median home values in different census tracts. Specifically, we are using a multiple linear regression model where the outcome variable is the natural logarithm of median home value. The natural log transformation is applied to the home values to stabilize variance and normalize the distribution of the values, which is common when dealing with skewed data like home prices. Later in this analysis, the data for median home value will be swapped out with emissions data as the outcome variable to investigate factors affecting emissions across different state however the follwoing analysis is conducted as exploratory.
Regression Equation
We are modeling the log of the median home value (\(\log(\text{median\_value})\)) as a function of several predictors, including:
The model is represented by the following equation:
\[ \log(\text{median\_value}) = \alpha + \beta_{1}(\text{median\_rooms}) + \beta_{2}(\text{median\_income}) + \beta_{3}(\text{pct\_college}) + \beta_{4}(\text{pct\_foreign\_born}) + \beta_{5}(\text{pct\_white}) + \beta_{6}(\text{median\_age}) + \beta_{7}(\text{median\_structure\_age}) + \beta_{8}(\text{percent\_ooh}) + \beta_{9}(\text{pop\_density}) + \beta_{10}(\text{total\_population}) + \epsilon \]
Here, \(\alpha\) is the intercept, and each \(\beta\) represents the coefficient for its respective predictor. The error term (\(\epsilon\)) captures any unexplained variation in the model.
In this section, we fit two linear regression models to examine the relationship between the log of the median home value and various explanatory variables. We present the coefficients, standard errors, t-values, and P-values for each model, along with a Variance Inflation Factor (VIF) analysis to assess multicollinearity.
# Define the formula for the linear model
formula <- "log(median_value) ~ median_rooms + median_income + pct_college + pct_foreign_born + pct_white + median_age + median_structure_age + percent_ooh + population_density + total_population"
# Fit the linear model
linear_model <- lm(formula = formula, data = dfw_data_for_model)
# Extract the summary of the linear model
model_summary <- summary(linear_model)
# Convert model coefficients to a dataframe for presentation
model_df <- as.data.frame(coef(model_summary))
# Add meaningful column names
colnames(model_df) <- c("Estimate", "Std. Error", "t value", "P-value")
# Ensure all values are formatted to 2 decimal places including P-values
model_df$Estimate <- round(model_df$Estimate, 3)
model_df$`Std. Error` <- round(model_df$`Std. Error`, 3)
model_df$`t value` <- round(model_df$`t value`, 3)
model_df$`P-value` <- ifelse(model_df$`P-value` < 0.001,
formatC(model_df$`P-value`, format = "e", digits = 3),
round(model_df$`P-value`, 3))
# Create a flextable with model summary
model_flextable <- flextable(model_df) %>%
set_caption("Linear Model Summary: Coefficients and Significance") %>%
autofit() %>%
colformat_num(j = c("Estimate", "Std. Error", "t value"), digits = 3) %>%
colformat_double(j = "P-value", digits = 3, big.mark = "") %>%
set_header_labels(
Estimate = "Estimate",
`Std. Error` = "Standard Error",
`t value` = "t-value",
`P-value` = "P-value"
)
# Display the flextable
model_flextableEstimate | Standard Error | t-value | P-value |
|---|---|---|---|
10.892 | 0.056 | 193.018 | 0.000e+00 |
-0.075 | 0.009 | -8.549 | 1.857e-17 |
0.000 | 0.000 | 25.794 | 6.345e-134 |
0.012 | 0.000 | 25.596 | 4.549e-132 |
0.008 | 0.001 | 8.763 | 2.985e-18 |
0.002 | 0.000 | 7.152 | 1.050e-12 |
0.003 | 0.001 | 2.925 | 0.003 |
0.000 | 0.000 | -10.185 | 5.174e-24 |
0.001 | 0.000 | 2.595 | 0.009 |
0.000 | 0.000 | 5.948 | 2.997e-09 |
0.000 | 0.000 | 11.316 | 3.709e-29 |
dfw_estimates <- dfw_data_for_model %>%
select(-GEOID, -median_value, -median_year_built) %>%
st_drop_geometry()
# Calculate correlations between variables and present. plot
correlations <- correlate(dfw_estimates, method = "pearson")
network_plot(correlations) # Present the VIF table
VIF_table <- vif(linear_model) %>%
as.data.frame() %>%
rownames_to_column("Variable") %>% # Convert rownames (variables) to a column
mutate(VIF = round(`.` , 3)) %>% # Round the VIF values to 2 decimal places
select(Variable, VIF) %>% # Ensure columns are correctly named
arrange(desc(VIF)) %>% # Sort by VIF
flextable() %>%
set_caption("Variance Inflation Factors (VIF)")
VIF_tableVariable | VIF |
|---|---|
median_income | 5.075 |
percent_ooh | 3.698 |
median_rooms | 3.218 |
pct_college | 3.085 |
pct_white | 2.532 |
population_density | 2.083 |
median_age | 1.710 |
pct_foreign_born | 1.708 |
median_structure_age | 1.404 |
total_population | 1.180 |
A VIF value of 1 indicates no collinearity; VIF values above 5 suggest a
level of collinearity that has a problematic influence on model
interpretation (James et al. 2013). VIF is implemented by the vif()
function in the car package (Fox and Weisberg 2019).
# Define the second formula for the linear model
formula_2 <- "log(median_value) ~ median_rooms + pct_college + pct_foreign_born + pct_white + median_age + median_structure_age + percent_ooh + population_density + total_population"
# Fit the second linear model
linear_model_2 <- lm(formula = formula_2, data = dfw_data_for_model)
# Extract the summary of the second linear model
model_summary_2 <- summary(linear_model_2)
# Convert model coefficients to a dataframe for presentation
model_df_2 <- as.data.frame(coef(model_summary_2))
# Add meaningful column names
colnames(model_df_2) <- c("Estimate", "Std. Error", "t value", "P-value")
# Format P-values in scientific notation where necessary and round other values to 3 digits
model_df_2$Estimate <- round(model_df_2$Estimate, 3)
model_df_2$`Std. Error` <- round(model_df_2$`Std. Error`, 3)
model_df_2$`t value` <- round(model_df_2$`t value`, 3)
model_df_2$`P-value` <- ifelse(model_df_2$`P-value` < 0.001,
formatC(model_df_2$`P-value`, format = "e", digits = 3),
round(model_df_2$`P-value`, 3))
# Create a flextable with model summary
model_flextable_2 <- flextable(model_df_2) %>%
set_caption("Linear Model Summary: Coefficients and Significance (Model 2)") %>%
autofit() %>%
colformat_num(j = c("Estimate", "Std. Error", "t value"), digits = 3) %>%
colformat_double(j = "P-value", digits = 3, big.mark = "") %>%
set_header_labels(
Estimate = "Estimate",
`Std. Error` = "Standard Error",
`t value` = "t-value",
`P-value` = "P-value"
)
# Display the flextable
model_flextable_2Estimate | Standard Error | t-value | P-value |
|---|---|---|---|
10.425 | 0.059 | 178.096 | 0.000e+00 |
0.026 | 0.009 | 2.992 | 0.003 |
0.021 | 0.000 | 59.943 | 0.000e+00 |
0.011 | 0.001 | 11.090 | 4.307e-28 |
0.003 | 0.000 | 8.542 | 1.976e-17 |
0.001 | 0.001 | 1.165 | 0.244 |
0.000 | 0.000 | -12.134 | 3.454e-33 |
0.004 | 0.001 | 8.356 | 9.378e-17 |
0.000 | 0.000 | 4.990 | 6.362e-07 |
0.000 | 0.000 | 11.495 | 5.106e-30 |
# Present the VIF table for the second model
VIF_table_2 <- vif(linear_model_2) %>%
as.data.frame() %>%
rownames_to_column("Variable") %>% # Convert rownames (variables) to a column
mutate(VIF = round(`.` , 2)) %>% # Round the VIF values to 2 decimal places
select(Variable, VIF) %>% # Ensure columns are correctly named
arrange(desc(VIF)) %>% # Sort by VIF
flextable() %>%
set_caption("Variance Inflation Factors (VIF) for Model 2")
# Display the VIF table
VIF_table_2Variable | VIF |
|---|---|
percent_ooh | 3.48 |
median_rooms | 2.58 |
pct_white | 2.51 |
population_density | 2.08 |
median_age | 1.70 |
pct_foreign_born | 1.68 |
pct_college | 1.42 |
median_structure_age | 1.39 |
total_population | 1.18 |
Principal Component Analysis (PCA) was conducted on the standardized data to reduce dimensionality and explore the relationships among the variables. The PCA summary includes the explained variance of each principal component, formatted into a table. The PCA loadings, which indicate the contribution of each variable to the principal components, were also retrieved. A bar plot of the PCA loadings was created to visualize the relationships between variables and principal components.
# Performing Principal Component Analysis on the standardized data
pca <- prcomp(formula = ~., data = dfw_estimates, scale. = TRUE, center = TRUE)
# Summarizing PCA results
pca_summary <- summary(pca)
# Formatting PCA results into a table for presentation
pca_table <- pca_summary$importance %>%
as.data.frame() %>%
rownames_to_column("Metric") %>%
mutate(Metric = ifelse(Metric == "Comp. 1", "PC1", "PC2")) %>%
# Rounding only numeric columns to 2 decimal places
mutate(across(where(is.numeric), ~round(., 2))) %>%
select(Metric, everything()) %>%
flextable() %>%
set_caption("PCA Summary for US Census Data: Explained Variance and Cumulative Proportion")
pca_tableMetric | PC1 | PC2 | PC3 | PC4 | PC5 | PC6 | PC7 | PC8 | PC9 | PC10 |
|---|---|---|---|---|---|---|---|---|---|---|
PC2 | 1.93 | 1.41 | 1.03 | 0.95 | 0.83 | 0.77 | 0.65 | 0.56 | 0.40 | 0.35 |
PC2 | 0.37 | 0.20 | 0.11 | 0.09 | 0.07 | 0.06 | 0.04 | 0.03 | 0.02 | 0.01 |
PC2 | 0.37 | 0.57 | 0.68 | 0.77 | 0.84 | 0.90 | 0.94 | 0.97 | 0.99 | 1.00 |
# Retrieving and formatting PCA loadings
pca_loadings_table <- pca$rotation %>%
as_tibble(rownames = "predictor") %>%
mutate(across(where(is.numeric), ~round(., 2)))
# Displaying PCA loadings
pca_loadings_table %>%
flextable() %>%
set_caption("PCA Loadings for US Census Data")predictor | PC1 | PC2 | PC3 | PC4 | PC5 | PC6 | PC7 | PC8 | PC9 | PC10 |
|---|---|---|---|---|---|---|---|---|---|---|
median_rooms | -0.37 | 0.25 | 0.09 | 0.47 | 0.18 | -0.36 | 0.03 | 0.10 | 0.59 | -0.24 |
total_population | -0.08 | 0.30 | 0.74 | 0.09 | -0.37 | 0.41 | -0.15 | 0.16 | -0.02 | -0.01 |
median_age | -0.34 | -0.21 | -0.08 | -0.13 | 0.55 | 0.61 | -0.05 | 0.35 | 0.16 | 0.06 |
median_income | -0.35 | 0.46 | -0.20 | 0.02 | -0.06 | -0.08 | 0.07 | 0.05 | -0.13 | 0.77 |
pct_college | -0.16 | 0.51 | -0.46 | -0.24 | -0.25 | 0.16 | 0.04 | 0.24 | -0.14 | -0.53 |
pct_foreign_born | 0.22 | 0.46 | 0.10 | -0.32 | 0.46 | -0.03 | -0.50 | -0.39 | 0.11 | -0.03 |
pct_white | -0.39 | -0.21 | -0.18 | -0.12 | -0.41 | 0.26 | -0.15 | -0.60 | 0.38 | 0.02 |
percent_ooh | -0.44 | 0.02 | 0.14 | 0.25 | 0.28 | 0.03 | 0.16 | -0.43 | -0.61 | -0.24 |
population_density | 0.36 | 0.28 | -0.03 | 0.14 | 0.12 | 0.38 | 0.68 | -0.29 | 0.23 | 0.03 |
median_structure_age | 0.27 | 0.04 | -0.35 | 0.70 | -0.05 | 0.30 | -0.44 | -0.02 | -0.12 | 0.04 |
# Plot the PCA loadings
pca_plot <- pca_loadings_table %>%
dplyr::select(predictor:PC5) %>%
pivot_longer(PC1:PC5, names_to = "component", values_to = "value") %>%
ggplot(aes(x = value, y = predictor)) +
geom_col(fill = "darkolivegreen4", color = "darkolivegreen4", alpha = 0.5) +
facet_wrap(~component, nrow = 1) +
labs(y = "Variable", x = "Value", title = "US Census Data PCA Loadings Barplot (5-Year ACS, 2015-2019)") +
theme_minimal() +
theme(axis.text.y = element_text(size = 8),
axis.text.x = element_text(size = 5),
axis.title = element_text(size = 10),
strip.text = element_text(size = 10),
plot.title = element_text(size = 12, hjust = 0.5)
)
print(pca_plot)The PCA component scores for each observation were calculated and combined with the original GEOID and median home value data. A spatial visualization of the first principal component (PC1) across regions was created to explore spatial patterns in the data. A linear model was then fit using the principal components as predictors to understand the relationship between the principal components and median home values. The results of the PCA-based regression model, including coefficients, standard errors, t-values, and p-values, are presented in the table below.
# Get PCA component scores for each observation
components <- predict(pca, dfw_estimates)
# Create a new dataframe combining the original GEOID and median_value with PCA components
dfw_pca <- dfw_data_for_model %>%
select(GEOID, median_value) %>%
cbind(components)
# Visualize the first principal component (PC1) across regions
ggplot(dfw_pca, aes(fill = PC1)) +
geom_sf(color = NA) +
theme_void() +
scale_fill_viridis_c() +
labs(title = "Spatial Visualization of Principal Component 1 (PC1)")# Construct a formula for regression using PC1 to PC6 as predictors
pca_formula <- paste0("log(median_value) ~ ", paste0('PC', 1:6, collapse = ' + '))
# Fit a linear model using the principal components as predictors
pca_model <- lm(formula = pca_formula, data = dfw_pca)
# Get a summary of the PCA-based regression model
pca_summary <- summary(pca_model)
# Convert model coefficients to a dataframe for presentation
pca_model_df <- broom::tidy(pca_model) %>%
mutate(
estimate = round(estimate, 2),
std.error = round(std.error, 2),
statistic = round(statistic, 2),
p.value = ifelse(p.value < 0.001, format(p.value, scientific = TRUE), round(p.value, 3))
)
# Create a flextable to present the PCA regression results
pca_model_flextable <- flextable(pca_model_df) %>%
set_caption("PCA-Based Regression Model Summary: Coefficients and Significance") %>%
autofit() %>%
colformat_num(j = c("estimate", "std.error", "statistic"), digits = 2) %>%
colformat_double(j = "p.value", digits = 2, big.mark = "") %>%
set_header_labels(
term = "Predictor",
estimate = "Estimate",
std.error = "Standard Error",
statistic = "t-value",
p.value = "P-value"
)
# Display the flextable
pca_model_flextablePredictor | Estimate | Standard Error | t-value | P-value |
|---|---|---|---|---|
(Intercept) | 12.03 | 0.01 | 2,345.25 | 0.000e+00 |
PC1 | -0.14 | 0.00 | -53.51 | 0.000e+00 |
PC2 | 0.27 | 0.00 | 74.10 | 0.000e+00 |
PC3 | -0.11 | 0.00 | -21.34 | 7.557e-95 |
PC4 | -0.14 | 0.01 | -25.65 | 1.407e-132 |
PC5 | -0.08 | 0.01 | -13.16 | 1.272e-38 |
PC6 | 0.09 | 0.01 | 13.30 | 2.277e-39 |
Spatial autocorrelation is an important diagnostic when dealing with geographical data. If residuals from a regression model are spatially autocorrelated, the assumption of independent errors in linear regression is violated, potentially leading to biased estimates and incorrect inferences. Moran’s I is commonly used to detect spatial autocorrelation in residuals. If the test shows significant spatial autocorrelation, this suggests that spatial models (such as spatial lag or error models) may be more appropriate than standard OLS models (Anselin 1988).
In this analysis, we check for spatial autocorrelation in the residuals of a simplified linear model using Moran’s I. We also visualize the distribution of residuals and their spatial lagged values to further explore spatial patterns.
# Add residuals to the dataset from the simplified linear model
dfw_data_for_model$residuals <- residuals(linear_model_2)
# Plot histogram of residuals to check their distribution
residuals_histogram <- ggplot(dfw_data_for_model, aes(x = residuals)) +
geom_histogram(bins = 100, alpha = 0.7, fill = "darkblue", color = "darkblue") +
theme_minimal() +
labs(title = "Histogram of Residuals", x = "Residuals", y = "Frequency") +
theme(plot.title = element_text(hjust = 0.5))
# Create spatial weights for neighbors
wts <- dfw_data_for_model %>%
poly2nb() %>%
nb2listw()
# Conduct Moran's I test for spatial autocorrelation
moran_test <- moran.test(dfw_data_for_model$residuals, wts)
# Add lagged residuals for spatial lag model visualization
dfw_data_for_model$lagged_residuals <- lag.listw(wts, dfw_data_for_model$residuals)
# Plot residuals vs lagged residuals to visualize spatial dependence
residuals_vs_lagged <- ggplot(dfw_data_for_model, aes(x = residuals, y = lagged_residuals)) +
theme_minimal() +
geom_point(alpha = 0.6, color = "royalblue3") +
geom_smooth(method = "lm", color = "darkblue", se = FALSE) +
labs(title = "Residuals vs Lagged Residuals", x = "Residuals", y = "Lagged Residuals") +
theme(plot.title = element_text(hjust = 0.5))
# Display the plots
print(residuals_histogram)## `geom_smooth()` using formula = 'y ~ x'
# Moran's I Test Results formatted as a table
moran_test_flextable <- as.data.frame(t(unclass(moran_test$estimate))) %>%
setNames(c("Observed Moran's I", "Expected Moran's I", "Variance")) %>%
rownames_to_column("Metric") %>%
flextable() %>%
set_caption("Moran's I Test for Spatial Autocorrelation in Residuals")
# Display Moran's I Test Results
moran_test_flextableMetric | Observed Moran's I | Expected Moran's I | Variance |
|---|---|---|---|
1 | 0.5265 | -0.0002992 | 0.0001109 |
In the following section, spatial regression techniques that account for spatial dependence in the data are run. Two primary types of spatial models—spatial lag models and spatial error models—are used to account for spatial autocorrelation.
Spatial Lag Model: This model includes a spatial lag of the outcome variable in the regression, allowing us to account for the influence of neighboring areas on the values in the current area. The spatial lag model introduces a spatially lagged dependent variable in the model’s right-hand side, and special estimation methods are used to avoid violating assumptions of independence.
Spatial Error Model: In contrast to the lag model, the spatial error model introduces spatial autocorrelation in the error term, capturing latent spatial processes that affect the outcome but aren’t directly included in the predictors.
The spatial lag model captures spatial dependence by including a spatial
lag of the dependent variable (log-transformed median home value) as a
predictor. This helps account for the possibility that neighboring
regions influence each other. The lagsarlm() function from the
spatialreg package is used to estimate this model.
# Define the spatial lag model
lag_model <- lagsarlm(
formula = formula_2,
data = dfw_data_for_model,
listw = wts
)
# Summarize the spatial lag model, including Nagelkerke's pseudo R-squared
lag_model_summary <- summary(lag_model, Nagelkerke = TRUE)
print(lag_model_summary)##
## Call:lagsarlm(formula = formula_2, data = dfw_data_for_model, listw = wts)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.2293707 -0.1289562 0.0085592 0.1311562 1.1104693
##
## Type: lag
## Coefficients: (asymptotic standard errors)
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 3.4476056535 0.1266919726 27.2125 < 0.00000000000000022
## median_rooms 0.0202824178 0.0059264169 3.4224 0.0006208
## pct_college 0.0104183118 0.0003193911 32.6193 < 0.00000000000000022
## pct_foreign_born 0.0036275336 0.0006677688 5.4323 0.00000005562619387
## pct_white 0.0009922264 0.0002351484 4.2196 0.00002447636080216
## median_age 0.0020736287 0.0006548608 3.1665 0.0015428
## median_structure_age -0.0000519025 0.0000062208 -8.3434 < 0.00000000000000022
## percent_ooh 0.0026979842 0.0003493322 7.7233 0.00000000000001132
## population_density 0.0000077125 0.0000017722 4.3519 0.00001349705341958
## total_population 0.0000260699 0.0000027635 9.4338 < 0.00000000000000022
##
## Rho: 0.6361, LR test value: 2232, p-value: < 0.000000000000000222
## Asymptotic standard error: 0.01124
## z-value: 56.62, p-value: < 0.000000000000000222
## Wald statistic: 3206, p-value: < 0.000000000000000222
##
## Log likelihood: 199.4 for lag model
## ML residual variance (sigma squared): 0.04757, (sigma: 0.2181)
## Nagelkerke pseudo-R-squared: 0.85
## Number of observations: 3343
## Number of parameters estimated: 12
## AIC: -374.8, (AIC for lm: 1855)
## LM test for residual autocorrelation
## test value: 21.7, p-value: 0.0000031904
##
## Moran I test under randomisation
##
## data: lag_model$residuals
## weights: wts
##
## Moran I statistic standard deviate = 3.7, p-value = 0.0001
## alternative hypothesis: greater
## sample estimates:
## Moran I statistic Expectation Variance
## 0.0388857 -0.0002992 0.0001108
The spatial error model captures spatial dependence in the error terms,
rather than in the predictors. It is useful when spatial correlation
affects the unexplained variation in the model. The errorsarlm()
function is used to estimate this model.
# Define the spatial error model
error_model <- errorsarlm(
formula = formula_2,
data = dfw_data_for_model,
listw = wts
)
# Summarize the spatial error model, including Nagelkerke's pseudo R-squared
error_model_summary <- summary(error_model, Nagelkerke = TRUE)
# Print the summary of the spatial error model
error_model_summary##
## Call:errorsarlm(formula = formula_2, data = dfw_data_for_model, listw = wts)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.2921154 -0.1142056 0.0055431 0.1182663 1.0262763
##
## Type: error
## Coefficients: (asymptotic standard errors)
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 10.7016488225 0.0518831521 206.2644 < 0.00000000000000022
## median_rooms 0.0405803540 0.0064137179 6.3271 0.000000000249781307
## pct_college 0.0142530485 0.0004148602 34.3563 < 0.00000000000000022
## pct_foreign_born 0.0043285243 0.0008621995 5.0203 0.000000515833533887
## pct_white 0.0038609661 0.0003866788 9.9849 < 0.00000000000000022
## median_age 0.0029114849 0.0006252446 4.6566 0.000003215471263696
## median_structure_age -0.0000554951 0.0000060287 -9.2051 < 0.00000000000000022
## percent_ooh 0.0014256720 0.0003545377 4.0212 0.000057899072719581
## population_density -0.0000105136 0.0000024748 -4.2482 0.000021546802292161
## total_population 0.0000204707 0.0000026114 7.8389 0.000000000000004441
##
## Lambda: 0.8525, LR test value: 2377, p-value: < 0.000000000000000222
## Asymptotic standard error: 0.01018
## z-value: 83.75, p-value: < 0.000000000000000222
## Wald statistic: 7014, p-value: < 0.000000000000000222
##
## Log likelihood: 271.9 for error model
## ML residual variance (sigma squared): 0.04105, (sigma: 0.2026)
## Nagelkerke pseudo-R-squared: 0.8563
## Number of observations: 3343
## Number of parameters estimated: 12
## AIC: -519.7, (AIC for lm: 1855)
##
## Moran I test under randomisation
##
## data: error_model$residuals
## weights: wts
##
## Moran I statistic standard deviate = -10, p-value = 1
## alternative hypothesis: greater
## sample estimates:
## Moran I statistic Expectation Variance
## -0.1081375 -0.0002992 0.0001108
The Lagrange Multiplier (LM) tests help detect the presence of spatial dependence in the residuals of an ordinary least squares (OLS) model. These tests help determine whether spatial error or spatial lag models are necessary.
# Perform Lagrange Multiplier (LM) tests for spatial dependence in residuals
lm_tests <- lm.LMtests(
model = linear_model_2, # OLS model
wts, # Spatial weights
test = c("LMerr", "LMlag", "RLMerr", "RLMlag") # Testing for spatial error and lag dependence
)
# Print the results of the LM tests
lm_tests##
## Rao's score (a.k.a Lagrange multiplier) diagnostics for spatial
## dependence
##
## data:
## model: lm(formula = formula_2, data = dfw_data_for_model)
## test weights: listw
##
## RSerr = 2496, df = 1, p-value <0.0000000000000002
##
##
## Rao's score (a.k.a Lagrange multiplier) diagnostics for spatial
## dependence
##
## data:
## model: lm(formula = formula_2, data = dfw_data_for_model)
## test weights: listw
##
## RSlag = 2371, df = 1, p-value <0.0000000000000002
##
##
## Rao's score (a.k.a Lagrange multiplier) diagnostics for spatial
## dependence
##
## data:
## model: lm(formula = formula_2, data = dfw_data_for_model)
## test weights: listw
##
## adjRSerr = 529, df = 1, p-value <0.0000000000000002
##
##
## Rao's score (a.k.a Lagrange multiplier) diagnostics for spatial
## dependence
##
## data:
## model: lm(formula = formula_2, data = dfw_data_for_model)
## test weights: listw
##
## adjRSlag = 403, df = 1, p-value <0.0000000000000002
The models addressed in the previous sections, including both the regular linear model and its spatial adaptations, estimate global relationships between the outcome variable (e.g., median home values) and its predictors. However, relationships between a predictor and the outcome variable observed for the entire region may vary significantly from neighborhood to neighborhood. This phenomenon is called spatial non-stationarity, and it can be explored using Geographically Weighted Regression (GWR).
Geographically Weighted Regression (GWR) is a spatial regression technique that allows the relationship between the dependent variable and independent variables to vary across space. GWR estimates local regression coefficients for each observation, providing insights into spatially varying relationships that may be masked in global regression models. In this analysis, we fit a GWR model to explore the spatially varying relationships between median home values and selected predictors.
GWR evaluates local variations in regression models using a kernel-based weighting function. The basic form of GWR for a given location \(i\) is:
\[ Y_i = \alpha_i + \sum\limits_{k=1}^m \beta_{ik} X_{ik} + \epsilon_i \]
where: - \(Y_i\) is the outcome at location \(i\), - \(\alpha_i\) is the location-specific intercept, - \(\beta_{ik}\) is the local regression coefficient for predictor \(k\), - \(\epsilon_i\) is the error term at location \(i\).
GWR uses a kernel bandwidth to compute the local regression model for each location. This bandwidth can be either fixed (based on a distance cutoff) or adaptive (using nearest neighbors). In our case, using Census tract data where the size of tracts varies widely, an adaptive kernel is preferred.
Fitting and Evaluating the GWR Model
The code below shows how to fit a GWR model with a defined formula and plot the maps of local R-squared values. Furthermore local parameter estimates for the percentage of owner-occupied housing, and local parameter estimates for population density are also included in order to provide insights into the spatially varying relationships between the predictors and median home values.
# Convert data to spatial format for GWmodel compatibility
dfw_data_sp <- dfw_data_for_model %>%
as_Spatial()
# Choose the bandwidth using cross-validation
bw <- bw.gwr(
formula = formula_2,
data = dfw_data_sp,
kernel = "bisquare",
adaptive = TRUE
)## Take a cup of tea and have a break, it will take a few minutes.
## -----A kind suggestion from GWmodel development group
## Adaptive bandwidth: 2073 CV score: 222.6
## Adaptive bandwidth: 1289 CV score: 200.7
## Adaptive bandwidth: 803 CV score: 185
## Adaptive bandwidth: 504 CV score: 166.6
## Adaptive bandwidth: 318 CV score: 155.3
## Adaptive bandwidth: 204 CV score: 149.2
## Adaptive bandwidth: 132 CV score: 147.2
## Adaptive bandwidth: 89 CV score: 225.5
## Adaptive bandwidth: 160 CV score: 147.3
## Adaptive bandwidth: 116 CV score: 147.2
## Adaptive bandwidth: 104 CV score: 147.9
## Adaptive bandwidth: 121 CV score: 147.1
## Adaptive bandwidth: 126 CV score: 147.2
## Adaptive bandwidth: 119 CV score: 147.1
## Adaptive bandwidth: 123 CV score: 147.1
## Adaptive bandwidth: 120 CV score: 147.1
## Adaptive bandwidth: 122 CV score: 147.1
## Adaptive bandwidth: 122 CV score: 147.1
# Fit the GWR model
gw_model <- gwr.basic(
formula = formula_2,
data = dfw_data_sp,
bw = bw,
kernel = "bisquare",
adaptive = TRUE
)
# Print the model results
gw_model_results <- gw_model$SDF %>%
st_as_sf()
# Plot the GWR results
ggplot(gw_model_results, aes(fill = Local_R2)) +
geom_sf(color = NA) +
scale_fill_viridis_c() +
theme_void() +
labs(title = "Local R-Squared Values from the GWR Model", fill = expression("Local R"^2)) +
theme(plot.title = element_text(hjust = 0.5))# Plot the local relationships between the percentage owner-occupied housing and median home values
ggplot(gw_model_results, aes(fill = percent_ooh)) +
geom_sf(color = NA) +
scale_fill_viridis_c() +
theme_void() +
labs(title = "Local β for the GWR Model (% Owner-Occupied Housing)",
fill = "Local β for \npercentage owner-occupied housing ")+
theme(plot.title = element_text(hjust = 0.5))# Explore this further by investigating the local parameter estimates for population density
ggplot(gw_model_results, aes(fill = population_density)) +
geom_sf(color = NA) +
scale_fill_viridis_c() +
theme_void() +
labs(title = "Local β for the GWR Model (Population Density)",
fill = "Local β for \npopulation density") +
theme(plot.title = element_text(hjust = 0.5))The statistical models discussed earlier were used to understand relationships between an outcome variable and a series of predictors. In the context of emissions analysis, these models are critical for identifying and understanding the factors contributing to environmental outcomes like air pollution or greenhouse gas emissions. Geodemographic clustering groups areas based on similarities in demographic and environmental factors, which can also be applied to emissions data. For example, regions with low emissions might cluster together, whereas areas with predominantly industrial emissions might form another cluster. Regionalization creates contiguous areas based on similarities in values, demographic factors, or other key indicators. This is particularly useful for spatial analysis, where regions with similar environmental/demographic trends can be grouped together. Below is an example using dimension reduction (principal component analysis) followed by k-means clustering to identify distinct geodemographic groups within the area of interest.
We use the k-means clustering algorithm to partition the dataset into
distinct groups. The k-means algorithm attempts to generate k clusters
that are internally similar but dissimilar from other clusters. In R,
the k-means clustering can be implemented with the kmeans() function.
Below is an example that demonstrates how we can use k-means to classify
regions based on principal component analysis (PCA) results. This helps
to reduce the dimensionality of the data while maintaining important
patterns.
# Setting seed for reproducibility
set.seed(123)
# Calculate statistical validation of the number of clusters (gap statistic)
#gap_stat <- clusGap(dfw_pca %>% st_drop_geometry() %>% select(PC1:PC8),
# FUN = kmeans, nstart = 25, K.max = 10, B = 50)
# Plot the gap statistic
#fviz_gap_stat(gap_stat) # 7 clusters seems to be the optimal number
# Perform k-means clustering on the PCA-transformed data (assume dfw_pca is created)
dfw_kmeans <- dfw_pca %>%
st_drop_geometry() %>%
select(PC1:PC8) %>%
kmeans(centers = 7)
# Assign the cluster IDs to the original dataset
dfw_clusters <- dfw_pca %>%
mutate(cluster = as.character(dfw_kmeans$cluster))
# Visualize the clusters on a map
ggplot(dfw_clusters, aes(fill = cluster)) +
geom_sf(size = 0.1) +
scale_fill_brewer(palette = "Set1") +
theme_void() +
labs(fill = "Cluster", title = "Geodemographic Clusters (K-Means Clustering)") +
theme(plot.title = element_text(hjust = 0.5))# Visualize the clusters on a plot using ggplotly for interactivity
cluster_plot <- ggplot(dfw_clusters,
aes(x = PC1, y = PC2, color = cluster)) +
geom_point() +
scale_color_brewer(palette = "Set1") +
theme_minimal()
ggplotly(cluster_plot) %>%
layout(legend = list(orientation = "h", y = -0.15,
x = 0.2, title = "Cluster")) %>%
config(displayModeBar = F) %>%
layout(title = "Geodemographic Clusters (K-Means Clustering)")# Create a data frame with the count of regions per cluster
cluster_counts <- as.data.frame(table(dfw_kmeans$cluster))
# Rename the columns for better readability
colnames(cluster_counts) <- c("Cluster", "Number of Regions")
# Create a flextable to display the cluster counts
cluster_flextable <- flextable(cluster_counts) %>%
set_caption("Number of Regions per Cluster") %>%
autofit()
# Display the table
cluster_flextableCluster | Number of Regions |
|---|---|
1 | 878 |
2 | 108 |
3 | 435 |
4 | 262 |
5 | 331 |
6 | 820 |
7 | 509 |
Spatial clustering is a technique used to identify spatial patterns in
data, grouping regions with similar characteristics together. In the
context of emissions analysis, spatial clustering can help identify
areas with similar emission profiles, which can be useful for targeted
policy interventions or resource allocation. In this section, we
demonstrate how to perform spatial clustering using the SKATER algorithm
(Assunção et al. 2006). This algorithm is implemented in R with the
skater() function in the spdep package and is also available in PySAL,
GeoDa, and ArcGIS as the “Spatially Constrained Multivariate Clustering”
tool.
# Prepare the input data for the SKATER algorithm by selecting the first 8 principal components
input_vars <- dfw_pca %>%
select(PC1:PC8) %>% # Select principal components (PC1 to PC8) from the PCA-transformed data
st_drop_geometry() %>% # Remove spatial (geometry) information to focus on numerical data
as.data.frame()
# Create a neighborhood structure (adjacency list) using Queen contiguity (neighboring polygons share an edge)
skater_nbrs <- poly2nb(dfw_pca, queen = TRUE)
# Calculate the "costs" (differences) between neighboring polygons based on the input variables
costs <- nbcosts(skater_nbrs, input_vars)
# Create a spatial weights object using the neighbor costs, with "B" style to set binary weights
skater_weights <- nb2listw(skater_nbrs, costs, style = "B")
# Generate a minimum spanning tree (MST) from the spatial weights object
mst <- mstree(skater_weights)
# Perform the SKATER algorithm to generate 7 regional clusters (using ncuts = 7), ensuring each region has at least 10 Census tracts (crit = 10)
#regions <- skater(
# mst[,1:2], # The first two columns of the MST (the edges of the tree)
# input_vars, # The input data (principal components)
# ncuts = 5, # Number of cuts (creates 9 regions)
# crit = 10 # Minimum number of tracts per region
# )
# Assign the resulting region labels (clusters) to the original spatial data frame
# dfw_clusters$region <- as.character(regions$group)
# Visualize the resulting regions on a map using ggplot2
# ggplot(dfw_clusters, aes(fill = region)) +
# geom_sf(size = 0.1) +
# scale_fill_brewer(palette = "Set1")
# theme_void() For the purpose of this analysis, we will download the American Community Survey (ACS) data for selected states and years. The ACS provides detailed demographic, social, economic, and housing data for the United States, making it a valuable resource for understanding regional characteristics. We will focus on the following states: Ohio (OH), Pennsylvania (PA), Tennessee (TN), West Virginia (WV), Kentucky (KY), Indiana (IN), and Illinois (IL). The data will be downloaded for the years 2005, 2010, and 2015 to capture changes over time.
# List of states for which to retrieve data
states <- c("OH", "PA", "TN", "WV", "KY", "IN", "IL")
# Variables to retrieve from the ACS
variables_to_get <- c(
# General wealth and housing indicators
median_value = "B25077_001", # Median home value
median_rooms = "B25018_001", # Median number of rooms
median_income = "DP03_0062", # Median household income
total_population = "B01003_001", # Total population
median_age = "B01002_001", # Median age
pct_college = "DP02_0068P", # Percent with Bachelor's degree or higher
pct_foreign_born = "DP02_0094P", # Percent foreign-born population
pct_white = "DP05_0077P", # Percent White population
median_year_built = "B25037_001", # Median year structure built
percent_ooh = "DP04_0046P", # Percent owner-occupied housing
# Income by race
median_income_black = "B19013B_001", # Median household income for Black or African American households
median_income_white = "B19013H_001", # Median household income for White (non-Hispanic) households
median_income_hispanic = "B19013I_001",# Median household income for Hispanic or Latino households
median_income_asian = "B19013D_001", # Median household income for Asian households
# Per capita income by race
per_capita_income_black = "B19301B_001", # Per capita income for Black or African American households
per_capita_income_white = "B19301H_001", # Per capita income for White (non-Hispanic) households
per_capita_income_hispanic = "B19301I_001",# Per capita income for Hispanic or Latino households
per_capita_income_asian = "B19301D_001" # Per capita income for Asian households
)
# Function to list all counties for a given state
list_counties_by_state <- function(state_abbreviation) {
fips_codes %>%
filter(state == state_abbreviation) %>%
pull(county)
}
# Years for which to retrieve ACS data (5-year estimates)
years <- seq(2009, 2020, by = 5)
# Initialize an empty list to store the data for each state and year
all_data <- list()
# Loop through each year, then through each state, and retrieve the ACS data
for (year in years) {
# Initialize a list to store data for this year
year_data_list <- list()
for (state in states) {
# List all counties in the current state
state_counties <- list_counties_by_state(state)
# Retrieve ACS data for the state's counties
state_data <- get_acs(
geography = "tract",
variables = variables_to_get,
state = state,
county = state_counties,
geometry = TRUE,
output = "wide",
year = year
) %>%
select(-NAME) %>% # Remove the NAME column
st_transform(crs = 5070) %>% # NAD83 / Conus Albers projection
mutate(dataset = paste0(year - 4, "-", year, " 5-year ACS"),
state = state) # Add a dataset and state column
# Append the state's data for this year to the list
year_data_list[[state]] <- state_data
}
# Combine the data for all states for this year
combined_year_data <- bind_rows(year_data_list)
# Append this year's data to the master list
all_data[[as.character(year)]] <- combined_year_data
}## Getting data from the 2005-2009 5-year ACS
## Fetching data by table type ("B/C", "S", "DP") and combining the result.
## Getting data from the 2005-2009 5-year ACS
## Fetching data by table type ("B/C", "S", "DP") and combining the result.
## Getting data from the 2005-2009 5-year ACS
## Fetching data by table type ("B/C", "S", "DP") and combining the result.
## Getting data from the 2005-2009 5-year ACS
## Fetching data by table type ("B/C", "S", "DP") and combining the result.
## Getting data from the 2005-2009 5-year ACS
## Fetching data by table type ("B/C", "S", "DP") and combining the result.
## Getting data from the 2005-2009 5-year ACS
## Fetching data by table type ("B/C", "S", "DP") and combining the result.
## Getting data from the 2005-2009 5-year ACS
## Fetching data by table type ("B/C", "S", "DP") and combining the result.
## Getting data from the 2010-2014 5-year ACS
## Fetching data by table type ("B/C", "S", "DP") and combining the result.
## Getting data from the 2010-2014 5-year ACS
## Fetching data by table type ("B/C", "S", "DP") and combining the result.
## Getting data from the 2010-2014 5-year ACS
## Fetching data by table type ("B/C", "S", "DP") and combining the result.
## Getting data from the 2010-2014 5-year ACS
## Fetching data by table type ("B/C", "S", "DP") and combining the result.
## Getting data from the 2010-2014 5-year ACS
## Fetching data by table type ("B/C", "S", "DP") and combining the result.
## Getting data from the 2010-2014 5-year ACS
## Fetching data by table type ("B/C", "S", "DP") and combining the result.
## Getting data from the 2010-2014 5-year ACS
## Fetching data by table type ("B/C", "S", "DP") and combining the result.
## Getting data from the 2015-2019 5-year ACS
## Fetching data by table type ("B/C", "S", "DP") and combining the result.
## Getting data from the 2015-2019 5-year ACS
## Fetching data by table type ("B/C", "S", "DP") and combining the result.
## Getting data from the 2015-2019 5-year ACS
## Fetching data by table type ("B/C", "S", "DP") and combining the result.
## Getting data from the 2015-2019 5-year ACS
## Fetching data by table type ("B/C", "S", "DP") and combining the result.
## Getting data from the 2015-2019 5-year ACS
## Fetching data by table type ("B/C", "S", "DP") and combining the result.
## Getting data from the 2015-2019 5-year ACS
## Fetching data by table type ("B/C", "S", "DP") and combining the result.
## Getting data from the 2015-2019 5-year ACS
## Fetching data by table type ("B/C", "S", "DP") and combining the result.
# Combine the data from all years into a single data frame
final_combined_data <- bind_rows(all_data)
# Ensure the geometry column is dropped correctly using st_drop_geometry()
flextable(
final_combined_data %>%
st_drop_geometry() %>% # Correctly remove the geometry column
head(15) # Select the first 15 rows
) %>%
set_caption("Census Tract-Level Data (Selected Variables), 5-year ACS") %>%
autofit() %>%
colformat_num(j = c("median_valueE", "median_valueM", "median_roomsE", "median_roomsM",
"median_incomeE", "median_incomeM", "total_populationE", "total_populationM",
"median_ageE", "median_ageM", "median_year_builtE", "median_year_builtM",
"pct_collegeE", "pct_collegeM", "pct_whiteE", "pct_whiteM",
"pct_foreign_bornE", "pct_foreign_bornM", "percent_oohE", "percent_oohM"),
digits = 2) %>% # Format numerical columns
set_header_labels(
GEOID = "Census Tract GEOID",
median_valueE = "Median Home Value Estimate",
median_valueM = "Median Home Value Margin of Error",
median_roomsE = "Median Rooms Estimate",
median_roomsM = "Median Rooms Margin of Error",
median_incomeE = "Median Income Estimate",
median_incomeM = "Median Income Margin of Error",
total_populationE = "Total Population Estimate",
total_populationM = "Total Population Margin of Error",
median_ageE = "Median Age Estimate",
median_ageM = "Median Age Margin of Error",
median_year_builtE = "Median Year Built Estimate",
median_year_builtM = "Median Year Built Margin of Error",
pct_collegeE = "Percent College-Educated Estimate",
pct_collegeM = "Percent College-Educated Margin of Error",
pct_whiteE = "Percent White Estimate",
pct_whiteM = "Percent White Margin of Error",
pct_foreign_bornE = "Percent Foreign-Born Estimate",
pct_foreign_bornM = "Percent Foreign-Born Margin of Error",
percent_oohE = "Percent Owner-Occupied Housing Estimate",
percent_oohM = "Percent Owner-Occupied Housing Margin of Error",
state = "State",
dataset = "Dataset"
)Census Tract GEOID | Median Home Value Estimate | Median Home Value Margin of Error | Median Rooms Estimate | Median Rooms Margin of Error | Total Population Estimate | Total Population Margin of Error | Median Age Estimate | Median Age Margin of Error | Median Year Built Estimate | Median Year Built Margin of Error | median_income_blackE | median_income_blackM | median_income_whiteE | median_income_whiteM | median_income_hispanicE | median_income_hispanicM | median_income_asianE | median_income_asianM | per_capita_income_blackE | per_capita_income_blackM | per_capita_income_whiteE | per_capita_income_whiteM | per_capita_income_hispanicE | per_capita_income_hispanicM | per_capita_income_asianE | per_capita_income_asianM | Median Income Estimate | Median Income Margin of Error | Percent College-Educated Estimate | Percent College-Educated Margin of Error | Percent Foreign-Born Estimate | Percent Foreign-Born Margin of Error | Percent White Estimate | Percent White Margin of Error | Percent Owner-Occupied Housing Estimate | Percent Owner-Occupied Housing Margin of Error | Dataset | State |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
39001990100 | 97,100 | 8,604 | 5.4 | 0.3 | 5,250 | 432 | 38.1 | 2.2 | 1,978 | 4 | 0 | 32,357 | 5,028 | 17,083 | 31,150 | 0 | 1,830 | 2,904 | 20,925 | 5,866 | 28,800 | 16,466 | 41 | 46 | 3,977 | 0 | 23.1 | 41.4 | 0.0 | 0.6 | 32.7 | 5.8 | 2005-2009 5-year ACS | OH | ||||
39001990200 | 96,100 | 5,683 | 5.6 | 0.2 | 4,615 | 343 | 38.4 | 3.9 | 1,974 | 3 | 0 | 35,318 | 3,539 | 0 | 0 | 19,435 | 2,964 | 36 | 41 | 3,317 | 0 | 100.0 | 57.1 | 0.0 | 0.7 | 28.1 | 4.9 | 2005-2009 5-year ACS | OH | |||||||||
39001990300 | 115,800 | 16,756 | 5.7 | 0.3 | 7,185 | 433 | 37.1 | 2.1 | 1,985 | 4 | 0 | 42,267 | 5,582 | 39,375 | 46,819 | 0 | 17,616 | 1,941 | 14,095 | 6,408 | 28 | 44 | 5,177 | 0 | 100.0 | 66.3 | 0.0 | 0.5 | 16.0 | 4.4 | 2005-2009 5-year ACS | OH | ||||||
39001990400 | 93,100 | 5,898 | 5.3 | 0.3 | 4,492 | 435 | 40.5 | 8.7 | 1,974 | 4 | 0 | 31,987 | 7,082 | 31,667 | 3,397 | 0 | 17,968 | 1,993 | 10,654 | 3,707 | 0 | 119 | 3,526 | 0 | 0.0 | 37.0 | 0.0 | 0.7 | 32.3 | 7.4 | 2005-2009 5-year ACS | OH | ||||||
39001990500 | 82,700 | 10,020 | 5.2 | 0.2 | 3,328 | 399 | 37.5 | 2.3 | 1,984 | 4 | 0 | 31,515 | 3,269 | 0 | 0 | 15,293 | 1,975 | 0 | 119 | 2,558 | 0 | 666,666,666.0 | 0.0 | 0.0 | 1.0 | 29.0 | 6.6 | 2005-2009 5-year ACS | OH | |||||||||
39001990600 | 76,200 | 10,572 | 5.1 | 0.3 | 3,272 | 327 | 41.0 | 3.0 | 1,973 | 3 | 0 | 26,403 | 4,853 | 0 | 0 | 0 | 14,550 | 1,577 | 7,835 | 2,695 | 10 | 15 | 2,542 | 0 | 100.0 | 100.0 | 0.0 | 1.0 | 29.8 | 5.6 | 2005-2009 5-year ACS | OH | ||||||
39003010100 | 134,400 | 13,332 | 6.4 | 0.3 | 4,346 | 207 | 31.2 | 6.2 | 1,963 | 6 | 0 | 59,412 | 7,928 | 0 | 0 | 6,681 | 5,125 | 24,353 | 3,044 | 15,556 | 12,965 | 32 | 27 | 3,538 | 0 | 29.3 | 25.6 | 0.0 | 0.7 | 25.1 | 5.5 | 2005-2009 5-year ACS | OH | |||||
39003010200 | 120,700 | 13,223 | 6.6 | 0.2 | 3,910 | 246 | 40.4 | 2.0 | 1,965 | 6 | 0 | 55,852 | 5,047 | 0 | 0 | 4,539 | 4,505 | 25,794 | 1,941 | 31,388 | 16,609 | 26 | 19 | 2,926 | 0 | 0.0 | 61.8 | 0.0 | 0.8 | 9.8 | 4.1 | 2005-2009 5-year ACS | OH | |||||
39003010300 | 151,200 | 26,070 | 6.5 | 0.5 | 1,617 | 118 | 40.5 | 2.5 | 1,967 | 15 | 0 | 52,198 | 5,907 | 0 | 0 | 22,399 | 2,405 | 0 | 119 | 1,160 | 0 | 666,666,666.0 | 0.0 | 0.0 | 2.0 | 14.0 | 7.9 | 2005-2009 5-year ACS | OH | |||||||||
39003010600 | 98,500 | 5,583 | 6.3 | 0.3 | 4,923 | 200 | 39.9 | 2.4 | 1,960 | 5 | 0 | 51,397 | 4,934 | 4,375 | 169,966 | 0 | 23,913 | 1,977 | 15,279 | 20,075 | 38 | 29 | 3,732 | 0 | 51.4 | 41.1 | 0.8 | 1.3 | 12.4 | 3.8 | 2005-2009 5-year ACS | OH | ||||||
39003010800 | 136,600 | 10,135 | 6.3 | 0.2 | 8,489 | 385 | 40.7 | 2.4 | 1,975 | 3 | 41,250 | 53,273 | 62,123 | 5,063 | 37,109 | 85,541 | 0 | 17,038 | 5,962 | 29,726 | 2,154 | 60,396 | 44,997 | 44,266 | 23,549 | 154 | 68 | 6,315 | 0 | 48.2 | 31.9 | 0.4 | 0.6 | 17.1 | 3.8 | 2005-2009 5-year ACS | OH | |
39003010900 | 126,300 | 9,740 | 5.9 | 0.4 | 4,793 | 747 | 34.6 | 8.5 | 1,970 | 3 | 41,439 | 20,637 | 49,639 | 5,290 | 12,404 | 29,985 | 0 | 21,468 | 4,235 | 26,084 | 3,788 | 6,712 | 3,526 | 38 | 28 | 3,900 | 0 | 100.0 | 36.3 | 0.0 | 0.7 | 24.8 | 5.4 | 2005-2009 5-year ACS | OH | |||
39003011000 | 96,700 | 11,326 | 5.0 | 0.4 | 5,429 | 593 | 32.3 | 3.6 | 1,977 | 3 | 24,042 | 20,562 | 36,869 | 3,885 | 102,500 | 44,650 | 0 | 13,625 | 6,532 | 20,485 | 2,248 | 14,209 | 10,386 | 10,463 | 12,275 | 0 | 119 | 4,284 | 0 | 100.0 | 22.0 | 1.4 | 2.0 | 52.5 | 6.3 | 2005-2009 5-year ACS | OH | |
39003011200 | 73,300 | 13,396 | 5.1 | 0.7 | 2,585 | 229 | 40.1 | 3.4 | 1,954 | 8 | 0 | 38,833 | 6,115 | 0 | 0 | 1,073 | 1,467 | 8,957 | 1,559 | 3,491 | 2,941 | 0 | 119 | 2,228 | 0 | 64.7 | 39.4 | 0.0 | 1.2 | 32.8 | 14.0 | 2005-2009 5-year ACS | OH | |||||
39003011300 | 135,900 | 6,753 | 6.1 | 0.2 | 6,699 | 243 | 40.2 | 3.4 | 1,972 | 2 | 23,750 | 29,122 | 58,310 | 5,072 | 0 | 0 | 10,340 | 5,206 | 25,967 | 2,130 | 40,985 | 41,488 | 24 | 27 | 5,029 | 0 | 84.1 | 28.9 | 0.0 | 0.5 | 15.0 | 4.7 | 2005-2009 5-year ACS | OH |
# List of variables to retrieve from the ACS
variables_to_get <- c(
median_value = "B25077_001",
median_rooms = "B25018_001",
median_income = "DP03_0062",
total_population = "B01003_001",
median_age = "B01002_001",
pct_college = "DP02_0068P",
pct_foreign_born = "DP02_0094P",
pct_white = "DP05_0077P",
median_year_built = "B25037_001",
percent_ooh = "DP04_0046P"
)
# Function to create maps and histograms for a state
create_maps_and_histograms <- function(state_abbreviation) {
# List all counties for the state
dfw_counties <- fips_codes %>%
filter(state == state_abbreviation) %>%
pull(county)
# Retrieve ACS data for the state
dfw_data <- get_acs(
geography = "tract", # get data at the tract level
variables = variables_to_get,
state = state_abbreviation,
county = dfw_counties,
geometry = TRUE,
output = "wide",
year = 2020
) %>%
select(-NAME) %>%
filter(!is.na(median_valueE)) # Remove missing values
# Create Median Home Value Map
mhv_map <- ggplot(dfw_data, aes(fill = median_valueE)) +
geom_sf(color = NA) +
scale_fill_viridis_c(labels = scales::label_dollar()) +
theme_void() +
labs(fill = "Median Home Value ($)", title = paste("Median Home Value Map -", state_abbreviation)) +
theme(axis.text=element_text(size=6),
plot.title = element_text(size=10),
axis.title = element_text(size=8),
legend.title = element_text(size = 8))
# Create Median Home Value Histogram
mhv_histogram <- ggplot(dfw_data, aes(x = median_valueE)) +
geom_histogram(alpha = 0.7, fill = "navy", color = "navy", bins = 100) +
theme_minimal() +
scale_x_continuous(labels = scales::label_dollar()) +
labs(x = "Median Home Value ($)", y = "Count", title = paste("Median Home Value Distribution -", state_abbreviation)) +
theme(axis.text=element_text(size=6),
plot.title = element_text(size=10),
axis.title = element_text(size=8),
legend.title = element_text(size = 8))
# Create Log-transformed Median Home Value Map
mhv_map_log <- ggplot(dfw_data, aes(fill = log(median_valueE))) +
geom_sf(color = NA) +
scale_fill_viridis_c() +
theme_void() +
labs(fill = "Log(Median Home Value)", title = paste("Log Median Home Value Map -", state_abbreviation))+
theme(axis.text=element_text(size=6),
plot.title = element_text(size=10),
axis.title = element_text(size=8),
legend.title = element_text(size = 8))
# Create Log-transformed Median Home Value Histogram
mhv_histogram_log <- ggplot(dfw_data, aes(x = log(median_valueE))) +
geom_histogram(alpha = 0.7, fill = "navy", color = "navy", bins = 100) +
theme_minimal() +
scale_x_continuous() +
labs(x = "Log(Median Home Value)", y = "Count", title = paste("Log Median Home Value Distribution -", state_abbreviation)) +
theme(axis.text=element_text(size=6),
plot.title = element_text(size=10),
axis.title = element_text(size=8),
legend.title = element_text(size = 8))
# Display all plots side-by-side
combined_plot <- (mhv_map + mhv_histogram) / (mhv_map_log + mhv_histogram_log)
# Print the combined plot to display
print(combined_plot)
}
# List of states to generate data and figures for
create_maps_and_histograms("PA")# List of variables to retrieve from the ACS
variables_to_get <- c(
per_capita_income_black = "B19301B_001", # Per capita income for Black population
per_capita_income_white = "B19301H_001", # Per capita income for White (non-Hispanic) population
per_capita_income_hispanic = "B19301I_001",# Per capita income for Hispanic population
per_capita_income_asian = "B19301D_001" # Per capita income for Asian population
)
# Function to create maps and histograms for income by race for a state
create_income_maps_and_histograms <- function(state_abbreviation) {
# List all counties for the state
state_counties <- fips_codes %>%
filter(state == state_abbreviation) %>%
pull(county)
# Retrieve ACS data for the state
income_data <- get_acs(
geography = "tract", # get data at the tract level
variables = variables_to_get,
state = state_abbreviation,
county = state_counties,
geometry = TRUE,
output = "wide",
year = 2020
) %>%
select(-NAME) # Remove the name column
# Create function to generate plots for each race, with filtering for NA values
create_plots_for_race <- function(race_col, race_label, color, log_color) {
# Filter out NAs for the specific race
income_data_race <- income_data %>%
filter(!is.na(!!sym(race_col)))
# Create Per Capita Income Map for the race
income_map <- ggplot(income_data_race, aes(fill = !!sym(race_col))) +
geom_sf(color = NA) +
scale_fill_viridis_c(labels = scales::label_dollar()) +
theme_void() +
labs(fill = "Per Capita Income ($)", title = paste("Per Capita Income (", race_label, ") -", state_abbreviation)) +
theme(axis.text=element_text(size=6),
plot.title = element_text(size=10),
axis.title = element_text(size=8),
legend.title = element_text(size = 8))
# Create Per Capita Income Histogram for the race
income_histogram <- ggplot(income_data_race, aes(x = !!sym(race_col))) +
geom_histogram(alpha = 0.7, fill = color, color = color, bins = 100) +
theme_minimal() +
scale_x_continuous(labels = scales::label_dollar()) +
labs(x = "Per Capita Income ($)", y = "Count", title = paste("Per Capita Income Distribution (", race_label, ") -", state_abbreviation)) +
theme(axis.text=element_text(size=6),
plot.title = element_text(size=10),
axis.title = element_text(size=8),
legend.title = element_text(size = 8))
# Log-transformed map for the race
income_map_log <- ggplot(income_data_race, aes(fill = log(!!sym(race_col)))) +
geom_sf(color = NA) +
scale_fill_viridis_c() +
theme_void() +
labs(fill = "Log(Per Capita Income)", title = paste("Log Per Capita Income (", race_label, ") -", state_abbreviation)) +
theme(axis.text=element_text(size=6),
plot.title = element_text(size=10),
axis.title = element_text(size=8),
legend.title = element_text(size = 8))
# Log-transformed histogram for the race
income_histogram_log <- ggplot(income_data_race, aes(x = log(!!sym(race_col)))) +
geom_histogram(alpha = 0.7, fill = log_color, color = log_color, bins = 100) +
theme_minimal() +
scale_x_continuous() +
labs(x = "Log(Per Capita Income)", y = "Count", title = paste("Log Per Capita Income Distribution (", race_label, ") -", state_abbreviation)) +
theme(axis.text=element_text(size=6),
plot.title = element_text(size=10),
axis.title = element_text(size=8),
legend.title = element_text(size = 8))
# Combine the map and histogram for both original and log-transformed data
combined_plot <- (income_map + income_histogram) / (income_map_log + income_histogram_log)
return(combined_plot)
}
# Create plots for each race (White, Black, Hispanic, Asian) and filter NAs for each race
white_plots <- create_plots_for_race("per_capita_income_whiteE", "White", "navy", "lightblue")
black_plots <- create_plots_for_race("per_capita_income_blackE", "Black", "darkred", "pink")
hispanic_plots <- create_plots_for_race("per_capita_income_hispanicE", "Hispanic", "darkgreen", "lightgreen")
asian_plots <- create_plots_for_race("per_capita_income_asianE", "Asian", "darkorange", "orange")
# Print the combined plots for all races
print(white_plots)
print(black_plots)
print(hispanic_plots)
print(asian_plots)
}
# List of states to generate data and figures for
create_income_maps_and_histograms("PA")## Getting data from the 2016-2020 5-year ACS
## Getting data from the 2016-2020 5-year ACS
## Getting data from the 2016-2020 5-year ACS
## Getting data from the 2016-2020 5-year ACS
## Getting data from the 2016-2020 5-year ACS
## Getting data from the 2016-2020 5-year ACS
## Getting data from the 2016-2020 5-year ACS
# List of states for which to retrieve data
states <- c("OH", "PA", "TN", "WV", "KY", "IN", "IL")
# Define the variables to retrieve from the ACS
variables_to_get <- c(
population = "B01003_001", # Total population
population_black = "B02001_003", # Total Black population
population_white = "B02001_002", # Total White (non-Hispanic) population
population_hispanic = "B03003_003", # Total Hispanic population
population_asian = "B02001_005", # Total Asian population
per_capita_income_black = "B19301B_001", # Per capita income for Black population
per_capita_income_black_moe = "B19301B_001M", # MOE for Black per capita income
per_capita_income_white = "B19301H_001", # Per capita income for White (non-Hispanic) population
per_capita_income_white_moe = "B19301H_001M", # MOE for White per capita income
per_capita_income_hispanic = "B19301I_001",# Per capita income for Hispanic population
per_capita_income_hispanic_moe = "B19301I_001M", # MOE for Hispanic per capita income
per_capita_income_asian = "B19301D_001", # Per capita income for Asian population
per_capita_income_asian_moe = "B19301D_001M" # MOE for Asian per capita income
)
# Function to retrieve and process data for each state
retrieve_data_for_county <- function(state_abbreviation) {
# List all counties in the state
state_counties <- list_counties_by_state(state_abbreviation)
# Retrieve ACS data for the state's counties
state_data <- get_acs(
geography = "county",
variables = variables_to_get,
state = state_abbreviation,
county = state_counties,
geometry = TRUE,
output = "wide",
year = 2020
) %>%
select(-NAME) %>%
st_transform(crs = 5070) %>%
mutate(state = state_abbreviation)
return(state_data)
}
# List of counties by state
list_counties_by_state <- function(state_abbreviation) {
fips_codes %>%
filter(state == state_abbreviation) %>%
pull(county)
}
# Retrieve data for all selected states
all_data <- lapply(states, retrieve_data_for_county)
# Combine data for all counties by state
percapita_income_combined_data_county <- bind_rows(all_data)
# Function to retrieve and process data for each state
retrieve_data_for_state <- function(state_abbreviation) {
# List all counties in the state
state_counties <- list_counties_by_state(state_abbreviation)
# Retrieve ACS data for the state's counties
state_data <- get_acs(
geography = "state",
variables = variables_to_get,
state = state_abbreviation,
county = state_counties,
geometry = TRUE,
output = "wide",
year = 2020
) %>%
select(-NAME) %>%
st_transform(crs = 5070) %>%
mutate(state = state_abbreviation)
return(state_data)
}
# List of counties by state
list_counties_by_state <- function(state_abbreviation) {
fips_codes %>%
filter(state == state_abbreviation) %>%
pull(county)
}
# Retrieve data for all selected states
all_data <- lapply(states, retrieve_data_for_state)
# Combine data for all states
percapita_income_combined_data_state <- bind_rows(all_data)
percapita_income_combined_data_county ## Simple feature collection with 619 features and 20 fields
## Geometry type: MULTIPOLYGON
## Dimension: XY
## Bounding box: xmin: 378600 ymin: 1342000 xmax: 1782000 ymax: 2295000
## Projected CRS: NAD83 / Conus Albers
## First 10 features:
## GEOID populationE populationM population_blackE population_blackM
## 1 39043 74419 NA 6779 403
## 2 39093 309134 NA 25104 911
## 3 39061 815790 NA 208444 1648
## 4 39007 97416 NA 3782 492
## 5 39167 60217 NA 794 150
## 6 39123 40557 NA 524 109
## 7 39079 32440 NA 326 149
## 8 39035 1241475 NA 364280 1820
## 9 39075 43954 NA 63 51
## 10 39095 430319 NA 81339 1500
## population_whiteE population_whiteM population_hispanicE
## 1 62990 552 3385
## 2 260049 1032 31425
## 3 542980 2030 28022
## 4 89870 471 4269
## 5 57606 141 666
## 6 38426 249 2105
## 7 31308 97 360
## 8 761770 2529 76316
## 9 43196 123 432
## 10 306681 1325 31680
## population_hispanicM population_asianE population_asianM
## 1 NA 578 90
## 2 NA 3558 324
## 3 NA 22196 842
## 4 NA 453 81
## 5 NA 452 84
## 6 NA 99 45
## 7 NA 0 26
## 8 NA 38471 890
## 9 NA 134 122
## 10 NA 7376 377
## per_capita_income_blackE per_capita_income_blackM per_capita_income_whiteE
## 1 17598 1798 37675
## 2 18031 1474 35144
## 3 21433 624 43872
## 4 12824 2437 26591
## 5 16966 6633 30987
## 6 19797 7732 39522
## 7 18898 9099 25389
## 8 20382 341 43115
## 9 10832 9983 24777
## 10 19408 805 34491
## per_capita_income_whiteM per_capita_income_hispanicE
## 1 2471 20509
## 2 828 18849
## 3 732 25788
## 4 1074 18318
## 5 2081 15058
## 6 5079 30165
## 7 1843 14333
## 8 506 21470
## 9 1330 39801
## 10 729 18477
## per_capita_income_hispanicM per_capita_income_asianE
## 1 2808 40996
## 2 1671 31329
## 3 2475 42874
## 4 6232 49647
## 5 4685 19133
## 6 8115 104428
## 7 2578 NA
## 8 1898 43310
## 9 14346 NA
## 10 1095 32771
## per_capita_income_asianM state geometry
## 1 13784 OH MULTIPOLYGON (((1093937 214...
## 2 5343 OH MULTIPOLYGON (((1128392 212...
## 3 3612 OH MULTIPOLYGON (((954051 1856...
## 4 15325 OH MULTIPOLYGON (((1233299 217...
## 5 12263 OH MULTIPOLYGON (((1203958 190...
## 6 66216 OH MULTIPOLYGON (((1095010 213...
## 7 NA OH MULTIPOLYGON (((1129149 184...
## 8 2432 OH MULTIPOLYGON (((1160561 212...
## 9 NA OH MULTIPOLYGON (((1151123 204...
## 10 5408 OH MULTIPOLYGON (((1061077 215...
## Simple feature collection with 7 features and 20 fields
## Geometry type: MULTIPOLYGON
## Dimension: XY
## Bounding box: xmin: 378600 ymin: 1342000 xmax: 1782000 ymax: 2295000
## Projected CRS: NAD83 / Conus Albers
## GEOID populationE populationM population_blackE population_blackM
## 1 39 11675275 NA 1442655 5444
## 2 42 12794885 NA 1419582 6251
## 3 47 6772268 NA 1128806 2966
## 4 54 1807426 NA 64285 1431
## 5 21 4461952 NA 361230 2429
## 6 18 6696893 NA 631923 3881
## 7 17 12716164 NA 1796660 5523
## population_whiteE population_whiteM population_hispanicE population_hispanicM
## 1 9394878 4978 459939 251
## 2 10155004 8675 971813 108
## 3 5196680 4158 377162 160
## 4 1672255 1658 28679 422
## 5 3848305 3113 167949 595
## 6 5510354 4802 475475 244
## 7 8874067 11289 2190696 236
## population_asianE population_asianM per_capita_income_blackE
## 1 268527 2412 21520
## 2 449320 2567 22440
## 3 122897 1790 22143
## 4 14228 743 20223
## 5 68139 1184 21623
## 6 158705 2039 21379
## 7 709567 3537 23954
## per_capita_income_blackM per_capita_income_whiteE per_capita_income_whiteM
## 1 275 35192 149
## 2 285 39275 191
## 3 345 33927 222
## 4 1106 27973 275
## 5 551 30608 225
## 6 503 33224 185
## 7 301 44581 194
## per_capita_income_hispanicE per_capita_income_hispanicM
## 1 20742 579
## 2 20089 446
## 3 17853 567
## 4 20871 1556
## 5 19047 662
## 6 19299 447
## 7 21679 224
## per_capita_income_asianE per_capita_income_asianM state
## 1 36982 821 OH
## 2 36970 761 PA
## 3 39809 2036 TN
## 4 36246 3192 WV
## 5 34915 2027 KY
## 6 32256 1186 IN
## 7 44968 922 IL
## geometry
## 1 MULTIPOLYGON (((1093937 214...
## 2 MULTIPOLYGON (((1287712 209...
## 3 MULTIPOLYGON (((514676 1342...
## 4 MULTIPOLYGON (((1155316 176...
## 5 MULTIPOLYGON (((583758 1514...
## 6 MULTIPOLYGON (((687449 1680...
## 7 MULTIPOLYGON (((378605 1916...